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Communication: concepts, practice and challenges †.

Disclaimer: Views expressed here are only those of the author and not those of World Health Organization (WHO).

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Davison Munodawafa, Communication: concepts, practice and challenges, Health Education Research , Volume 23, Issue 3, June 2008, Pages 369–370, https://doi.org/10.1093/her/cyn024

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Communication involves transmission of verbal and non-verbal messages. It consists of a sender, a receiver and channel of communication. In the process of transmitting messages, the clarity of the message may be interfered or distorted by what is often referred to as barriers.

Health communication seeks to increase knowledge gain. This is the minimum expectation and acceptable requirement to demonstrate that learning has taken place following an intervention using communication. Once knowledge gain is established, it is assumed that the individual will use the knowledge when the need arises or at an opportune time. There is evidence in several school-based health interventions demonstrating that young people who got exposed to specific information, e.g. against smoking or engaging in harmful practice, tended to posses decision or refusal skills.

Communication requires full understanding of behaviors associated with the sender and receiver and the possible barriers that are likely to exist. There are also challenges with establishing the source of what is to be communicated since this is a pre-requisite for program success. Often, communication (i.e. messages) originated from professionals or the government and ignore involving the intended beneficiaries. As a result, those communication activities seeking to impart knowledge and skills and/or behavior change often fail to realize the ultimate goal of behavior change because the beneficiaries find no relevancy in the activities.

Communication processes can be classified into two categories namely (i) mass media and (ii) Group media. Mass media focuses on reaching a wide audience while the group media reaches a specific group with clearly defined characteristics. Radio, television and Internet are examples of mass media channels while drama, storytelling, music and dance fall under group media.

Selecting a communication channel requires a complete understanding of the strengths, limitations and possible solutions related to each potential channel. Those entrusted with developing health education interventions that require communication need to be aware of the limitations in order to identify other complimentary activities to be able to achieve desired results. The context in which communication takes place is a major determinant to achieving the desired results. First, there should be a situational analysis conducted which includes also an audience analysis and this could be a rapid or comprehensive assessment. The findings of a situational analysis are then fed into decisions regarding the appropriate messages and channels to be applied. The situational analysis presents opportunities for implementing multiple communications where necessary.

In order to succeed in establishing effective health interventions using communication, the participation of intended beneficiaries throughout the programme phases is a pre-requisite. In other words, the intended beneficiaries should participate in setting objectives, selecting activities as well as monitoring of the effectiveness of the activities and participate in the planning and implementation. The beneficiaries should also be a part of establishing an environment that is conducive to delivering effective communication activities. In order to realize this goal in programme terms, policies and legislations that promote communication are required at national level. In many countries, mass media outlets such as television, radio, internet and newspapers are either a State monopoly or are under the ownership of private companies thereby making it hard for public service organizations to easily access them. The high fees levied for using these information outlets is quite prohibitive to most public health services organizations particularly those operating at community level.

Communication is not a panacea for all public health concerns and therefore expectations should be realistic. To guarantee that communication is being applied appropriately, the situational analysis findings should inform the next steps as discussed earlier. In this regard, it is essential to distinguish whether the problem or concern is not linked to lack of policy or legislation and not necessarily communication. Communication has been considered a failure in certain situations when, in fact, the problem required a policy or legislative remedies and not communication. The identification of predisposing, enabling and reinforcing factors to knowledge acquisition and behavior change should guide communication processes.

In some cases, public health problems encountered by the community are policy, economic or political related, and no amount of communication would influence change because there is need for a policy or political decision.

Communication approaches that provide opportunities for interpersonal interaction are likely to yield desired behavior change. These interpersonal group communications include drama, song, story telling and debate among others. The interpersonal communication can take into consideration social, cultural and behavioral factors that influence health outcomes unlike with mass media.

Communication conveys complex, sensitive and controversial information. It is critical that those responsible for facilitating information dissemination receive training in handling sensitive or controversial issues in order not to diminish the possible gains from communication.

Ultimately, credibility of the source of information is highly correlated with achievement of desired behavior outcomes. Those involved in communicating vital health information should ascertain that they are credible sources of information among the public. All content to be communicated should be thoroughly verified in order to avoid misinformation or sending conflict misinformation or sending conflict messages because once something is communicated, it can not be recalled ‘ uncommunicated’. In other words, a retraction of a statement or any apology does not mean that communication did not take place or what was communicated has been erased. It remains as a record despite the retraction. Guarantee freedom to communicate by not allowing any form of put-down or unconstructive criticism before, during and after communication.

Last but not least, listening is part of communication. Unfortunately, it is rarely taught formally and also neither is it acknowledged during development of communication interventions. In order for one to listen effectively, it is a must that one does not appear to be impatient or in a hurry. Both persons should allow each other to freely communicate without interference.

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The Scholarly Communication Handbook

From research dissemination to societal impact.

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Where is the best place to publish academic research now? Scholarly communication covers a broad range of topics and issues, and advances in online platforms and tools for research support have led to unprecedented changes in publishing options, research assessments and research policies. As a result, researchers are facing a transformed scholarly communication landscape, making research dissemination and societal impact a complex topic. Guided by the question, 'where to publish?', The Scholarly Communication Handbook explores publication types, open access and licensing options, as well as appropriate uses of research metrics and the benefits and setbacks of peer review. It answers questions such as: 'what are the key considerations for exploring new publication venues and experimenting with new forms of publishing?'; 'why are research metrics and open research important topics in scholarly communication?'; and 'how can scholarly communication librarians and researchers prepare for future changes in scholarly publishing?'. The book will provide a comprehensive overview of the knowledge required for understanding and navigating the scholarly communication landscape. Critical issues about research integrity, bibliodiversity and sustainability are also addressed to provoke discussions and debates about the future of scholarly publishing and communication. Readers will be empowered not just to make informed decisions about where they publish, but also understand policy changes and advocacy work in relation to research and publication processes. This will be an ideal book for researchers, students alike who aspiring to or currently working in academic libraries and the teams who support them.

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Frontmatter pp i-iv

Contents pp v-viii, figures and tables pp ix-x, about the author pp xi-xii, preface pp xiii-xvi, acknowledgements pp xvii-xviii, list of abbreviations pp xix-xx, 1 - the scholarly communication landscape pp 1-10, 2 - publication types pp 11-26, 3 - open access pp 27-40, 4 - copyright and licence to publish pp 41-50, 5 - peer review pp 51-62, 6 - research metrics pp 63-76, 7 - societal impact pp 77-90, 8 - research integrity pp 91-102, 9 - critical issues and the future of scholarly communication pp 103-114, case studies pp 115-120, references pp 121-130, index pp 131-133, full text views.

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SPECIALTY GRAND CHALLENGE article

Understanding and navigating the scholarly communication landscape in the twenty-first century.

• School of Information Studies, University of Wisconsin-Milwaukee, Milwaukee, WI, United States

What is scholarly communication? We lack a universally accepted definition. The Association for College and Research Libraries (ACRL), however, provides a broad perspective:

“Scholarly communication is the system through which research and other scholarly writings are created, evaluated for quality, disseminated to the scholarly community, and preserved for future use. The system includes both formal means of communication, such as publication in peer-reviewed journals, and informal channels, such as electronic mailing lists” ( ACRL Scholarly Communications Committee, 2003 ).

There is no doubt that scholarly communication is a fundamental activity in all scholarly disciplines. Without this system there would be no networks of scholars, dissemination outlets, and the wealth of recorded scholarship would not be available to readers. Simply put, today's knowledge could not advance without scholarly communication. Despite the long history of formal methods for communication, research on how scholars communicate, and the different facets of this system, are needed more than ever. We have entered an exciting and tumultuous time where the research community is grappling with issues that span social and technological concerns. These concerns, in turn, affect the processes and products of scholarly communication that impact the publishers of scholarly works and distributors such as libraries.

Formal processes for scholarly communication have evolved over the centuries, aided by technological developments, and shaped by ideological shifts. Industries and associations have developed around facilitating scholarly communication whether through journals, conferences and associated proceedings, or monographic treatments of research topics. Technologies and new mindsets are transforming—and challenging—traditional systems for the publication and dissemination of scholarly products. One cannot overstate the importance of information and communication technologies (ICTs) for scholars in reducing the barriers of distance and time. Throughout history, the exchange of ideas could only take place as quickly as the fastest mode of delivery. ICTs, ultimately, have made this communication essentially instantaneous, where distance is no longer an obstacle to the sharing of ideas or facilitation of collaborations among scholars across multiple countries.

Similarly, the technologies used to record scholarly discourse, and to collect and store the evidence used in support of research, make it possible to pursue topics on a scale that could only be imagined even a few decades ago. Big data and big science projects now require the efforts of large interdisciplinary teams of researchers who work toward a common goal as part of centralized or decentralized teams. The resources needed to support large projects present their own challenges for researchers, the institutions in which they operate, and the funding agencies that support their work.

Despite the key role of technologies for the storage and dissemination of scholarly products, the system of scholarship is still is most importantly about human-centered activities. Technologies simply provide the tools to facilitate storage, communication, dissemination, and collaboration. The process of scholarship, in turn, is shaped by the environment in which it exists and is influenced by associated cultural norms and ethics of the scholarly community.

How we communicate with colleagues within our disciplines and in other disciplines, and increasingly how what is learned is translated to the public, are more important than ever for accountability and transparency. The Open Science movement encourages all aspects of scholarly activity to be open ( de la Fuente, 2018 ). This movement has been most evident through Open Access publications, where authors or publication venues make the products of scholarship freely accessible to a global audience. Open Science is expanding further to include open datasets, researcher notes, open software, and open peer assessment of scholarly products. Openness encourages accessibility, accountability, reuse, reproducibility, and transparency. This, then, encourages further discovery and understanding. However, the push toward openness can be a double-edged sword. In some disciplinary areas, particularly involving social research, the move for openness must be balanced with the equally important considerations of privacy and confidentiality of personal and social data. This concern extends to big data, where opportunities to discover knowledge can also raise ethical concerns.

Ethical issues are at the forefront of scholarly communication and affect all aspects of scholarly processes. As scholars we strive to reveal and understand the world around us. Increasing pressures for researchers to “produce” have promoted an environment of “publish or perish,” which creates the potential for research misconduct or ethically questionable behavior. The outcomes of the pressures to produce manifest themselves in many forms and may include: the reporting of slipshod research, a focus on the least publishable unit, gratuitous authorship, data fabrication, plagiarism, and selective reporting of results. In scholarly environments where prestige and impact are determined, at least in part, by measures based on citations and other usage data, these pressures extend to journal editors and publishers where increasing the profile of a journal to attract the best submissions presents its own challenges. These issues also extend to peer review, a cornerstone of scholarly communication. With the growing numbers of venues that publish reviewed research, demands on scholars' time to participate in rigorous peer review are increasing ( Kovanis et al., 2016 ).

How we assess scholars and scholarship represents another important facet of scholarly communication in need of further study. Scholarly reward systems encompass both the recognition (or credit) that scholars receive for their contributions as well as the tangible and intangible rewards bestowed upon them that can help advance their careers and stature in the research community. In addition, understanding how scholars remain current and how they engage in information seeking behavior is vital to effective scholarly communication. The growth in the amount of scholarly literature published annually makes it increasingly difficult for researchers to keep up with developments in their own fields, let alone allied disciplines.

With these topics in mind, the Scholarly Communication section of Frontiers in Research Analytics and Metrics provides a forum for all aspects of scholarly communication—past, present, and future—that address the stakeholders, processes, products, and the environments in which they exist. We welcome original research submissions that investigate how the changing landscape of scholarship is created and communicated in the sciences, social sciences and humanities, and we encourage interdisciplinary and multidisciplinary perspectives that focus on any of these issues.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

ACRL Scholarly Communications Committee (2003). Principles and Strategies for the Reform of Scholarly Communication . Available online at: http://www.ala.org/acrl/publications/whitepapers/principlesstrategies (accessed October 25, 2019).

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de la Fuente, G. B. (2018). What is Open Science? Introduction . Available online at: https://www.fosteropenscience.eu/content/what-open-science-introduction (accessed October 25, 2019).

Kovanis, M., Porcher, R., Ravaud, P., and Trinquart, L. (2016). The global burden of journal peer review in the biomedical literature: strong imbalance in the collective enterprise. PLoS ONE 11:e0166387. doi: 10.1371/journal.pone.0166387

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Keywords: research ethics, scholarly communication, big data, research collaboration, open science, research assessment

Citation: Wolfram D (2019) Understanding and Navigating the Scholarly Communication Landscape in the Twenty-First Century. Front. Res. Metr. Anal. 4:4. doi: 10.3389/frma.2019.00004

Received: 17 October 2019; Accepted: 30 October 2019; Published: 13 November 2019.

Edited and reviewed by: Chaomei Chen , Drexel University, United States

Copyright © 2019 Wolfram. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Dietmar Wolfram, dwolfram@uwm.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Research Article

Using interpersonal communication strategies to encourage science conversations on social media

Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation Ocean Frontier Institute, Dalhousie University, Halifax, Nova Scotia, Canada

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – review & editing

Affiliation School of Information Management, Dalhousie University, Halifax, Nova Scotia, Canada

• Curtis Martin, 
• Bertrum H. MacDonald

• Published: November 10, 2020
• https://doi.org/10.1371/journal.pone.0241972
• Reader Comments

Today, many science communicators are using social media to share scientific information with citizens, but, as research has shown, fostering conversational exchanges remains a challenge. This largely qualitative study investigated the communication strategies applied by individual scientists and environmental non-governmental organizations on Twitter and Instagram to determine whether particular social media practices encourage two-way conversations between science communicators and citizens. Data from Twitter and Instagram posts, interviews with the communicators, and a survey of audience members were triangulated to identify emergent communication strategies and the resulting engagement; provide insight into why particular practices are employed by communicators; and explain why audiences choose to participate in social media conversations with communicators. The results demonstrate that the application of interpersonal communication strategies encourage conversational engagement, in terms of the number of comments and unique individuals involved in conversations. In particular, using selfies (images and videos), non-scientific content, first person pronoun-rich captions, and responding to comments result in the formation of communicator-audience relationships, encouraging two-way conversations on social media. Furthermore, the results indicate that Instagram more readily supports the implementation of interpersonal communication strategies than Twitter, making Instagram the preferred platform for promoting conversational exchanges. These findings can be applicable to diverse communicators, subjects, audiences, and environments (online and offline) in initiatives to promote awareness and understanding of science.

Citation: Martin C, MacDonald BH (2020) Using interpersonal communication strategies to encourage science conversations on social media. PLoS ONE 15(11): e0241972. https://doi.org/10.1371/journal.pone.0241972

Editor: Rashid Mehmood, King Abdulaziz University, SAUDI ARABIA

Received: October 3, 2019; Accepted: October 24, 2020; Published: November 10, 2020

Copyright: © 2020 Martin, MacDonald. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: “Ethical approval for this study was obtained at Dalhousie University, which operates within the terms of the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – TCPS 2 (2018). In compliance with this ethics approval, which assured anonymity and confidentiality to all participants, the original data cannot be made available. As the text of the Twitter and Instagram posts assembled could be searched online and the participants thereby disclosed, de-identifying the social media data is not possible. Similarly, the interview transcripts contain specific information related to the social media practices of each of the communicators, and could be used to identify the individual or organization participants. However, all anonymized aggregate data from the survey, as well as anonymized quotations from the interviews and survey, necessary to replicate the study’s results are within the manuscript and its Supporting Information files.”

Funding: BHM 435-2015-1705 Social Sciences and Humanities Research Council of Canada http://www.sshrc-crsh.gc.ca/home-accueil-eng.aspx The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Human activities—both past and present—are having detrimental impacts on the earth’s environmental systems: fishing practices have forced fish stocks to critical condition [ 1 ], many of the planet’s species are being driven to extinction at an alarming rate [ 2 ], and continuous burning of fossil-fuels has created a global climate emergency [ 3 ]. If these harmful environmental practices are to be mitigated, they need to be managed through policy decisions at the science-policy interface where various actors, barriers, and enablers affect the flow of information from researchers to decision-makers [ 4 ]. Citizens are an important group that interacts with numerous stakeholders at this interface. If citizens are to be effective participants in decisions and solutions to address deteriorating environmental conditions, relevant research information must be communicated effectively to this diverse group. However, this communication is not a trivial activity, as cultivating environmental science literacy has proven to be a major challenge [ 5 – 8 ]. Climate change literacy is often cited to illustrate this challenge; misunderstanding is still widespread among citizens, due to a combination of denial, intentional obfuscation of facts, and personal values taking precedent over scientific information [ 5 , 6 , 9 , 10 ].

Although risks are associated with communicating science via social media (such as being subject to internet trolls and anti-science users [e.g., 11 , 12 ]), the internet and social media provide science communicators with significant opportunities to share policy-relevant information with citizens, as such tools are now the main information source for the public, including for scientific and policy information [ 13 , 14 ]. As of 2019 an estimated 4.4 billion people use the internet, with nearly 3.5 billion active on social media [ 15 ]. The latest statistics show that billions of social media posts are created daily on Facebook, Twitter, Instagram, YouTube, and other social media platforms, and the numbers are increasing [ 15 , 16 ]. Although important barriers to internet access still exist [e.g., 17 , 18 ], new media are generally user-friendly and widely available; simple and quick web searches can break down technical and financial barriers to information, and social media platforms are primarily inexpensive and accessible internationally [ 19 , 20 ]. Virtual communities can be formed online to facilitate public engagement with science, and citizens now have greater opportunity to participate in science communication, bypassing traditional information “gatekeepers” (e.g., scientific journals, popular media, government reports) to aid in information dissemination, and increase public awareness of important scientific issues [ 19 , 21 – 23 ].

Numerous researchers have explored whether relationships exist between social media posting behaviours of communicators and audience engagement [e.g., 24 – 30 ]. Research on this subject has been mainly exploratory to date, with studies covering a range of social media platforms and methods. At present, the results indicate that communication techniques can play an important role in generating audience engagement for both individual and organization communicators, but that science communicators have typically struggled to encourage conversations on social media, particularly with citizens exposed to such information for the first time [ 31 – 33 ]. Some studies have noted that science communicators have given lower priority to strategies that would promote engagement via online conversations [ 34 ]. Researchers have called for further exploration to understand better the challenges of facilitating science conversations on social media, to identify additional means of improving engagement, and to investigate whether communicator strategy and audience engagement patterns persist across communication topics [ 25 , 29 , 30 , 35 ]. In particular, they have called for small scale studies that offer detailed insights that big data approaches are less likely to provide [ 35 ].

This study applied a mixed methods approach to investigate communication strategies and two-way conversation activities of individual and non-governmental organization science communicators on two different social media platforms (Twitter and Instagram). The study triangulated data obtained through qualitative methods to: identify emergent communication strategies and resulting audience engagement; gain insight into why particular practices are employed by communicators; and determine why members of the audiences choose to participate in social media conversations with communicators.

Literature review

Science communication on social media.

The ability to communicate science to a wide variety of audiences is important. Scientific information is often needed for effective policy decisions, and strong science communication can promote the use of relevant information in environmental decisions [ 4 , 36 , 37 ]. Scientific information should be actively shared with citizens. Not only is the majority of scientific research publicly funded, citizens also need access to scientific information to make informed input to decisions on subjects relating to public policy, technological advancement, political preferences, and personal environmental practices, among others [ 26 , 38 – 42 ]. Communicating science to audiences beyond the academic community is increasingly seen as a responsibility of scientists, and is in some cases central to receiving research funding [ 40 , 43 – 45 ].

Scientists have been turning to social media to communicate the results of their research [ 46 , 47 ]. These media are significant because they grant communicators a platform for two-way exchanges with members of the public. Previously, the common and accepted communication model was based on resolving a perceived knowledge deficit to improve public understanding of science [ 48 – 50 ]. In this “first-order” way of thinking it was assumed that citizens lacked knowledge and acted as passive receivers of information. Thus, solely providing people with the necessary information was intended to lead to greater understanding and awareness of public issues [ 48 , 49 , 51 , 52 ]. “Second-order” communication that is reflexive, deliberative, and depends on dialogic, two-way information exchange is now thought to be a better model for sharing information with citizens [ 49 , 51 , 52 ]. This latter model promotes knowledge co-production between researchers and citizens by allowing people to bring their ideas and values to the conversation, and facilitates the formation of trust relationships between researchers and citizens [ 48 , 49 , 53 – 56 ]. A third participation model of science communication has also been proposed in the belief that all involved can contribute to decisions that affect them [ 57 , 58 ]. Social media—including blogs, microblogs, social networks, podcasts, and curatorial tools—offer the potential to facilitate deliberative communications, allowing citizens to participate in research discussions online by responding to information, sharing it with others, and/or creating new science communication resources [ 46 , 59 , 60 ].

Non-governmental organizations and individual scientists as communicators on social media

Social media have become significant to organizational practice [ 61 – 63 ]. Non-governmental organizations (NGOs) in particular have been credited with pioneering the use of social networking tools, prior to their use by government agencies and private companies [ 64 ]. As a result, social media—including Twitter and Instagram—are used by many NGOs around the world. According to a recent report, 77% of NGOs use Twitter, and 50% use Instagram, with the majority posting on both Twitter and Instagram at least once per week [ 64 ]. NGOs of all sizes are reaching large numbers on both platforms with some building massive audiences. For example, Amnesty International has over 1 million Twitter followers ( www.twitter.com/amnesty ), and over 500,000 Instagram followers ( www.instagram.com/amnesty ).

NGOs cite numerous benefits associated with social media use, including fundraising, increased brand awareness, volunteer recruitment, improved event organization, and more effective communications [ 64 – 66 ]. Through social media, organizations can share information, participate in conversations, and build relationships with their audiences [ 65 – 68 ]. Nonetheless, various studies show that NGOs have not fully capitalized on the affordances granted by social media: organizations have typically been found to focus on one-way communication models characteristic of a knowledge-deficit, using social media primarily as a broadcast tool, similar to the practices observed for some government agencies [ 25 , 29 , 68 – 72 ].

Individual scientists have been relatively slow in adopting social media [ 73 – 77 ]. According to a survey by Nature, an estimated 13% of scientists use Twitter regularly, with 50% of those engaging in scientific discussions on the platform [ 78 ]. According to another study, it is estimated that a smaller portion of scientists active on Twitter also use Instagram [ 79 ]. One reason for slow acceptance is that science outreach is often not incentivized for researchers; researchers interested in communication activities are therefore often required to pursue them on a volunteer basis in addition to their professional duties, creating a time barrier [ 79 , 80 ]. Furthermore, scientists—especially those working in government and industry—are sometimes discouraged from open communications [e.g., 81 – 83 ]. In other words, broad and public communication is typically not regarded as a valuable activity for researchers [ 79 ]. There is also evidence that individual scientists avoid communicating via the tools due to a general lack of knowledge on how the tools function, questions surrounding the rigor of scientific discussions on social media, and incorrect perceptions that the tools are ineffective as a means of scientific communication [ 75 – 77 , 79 ].

Numerous studies have demonstrated the strong communication potential that social media provide to scientists [e.g., 84 – 86 ]. Social media afford scientists the ability to build their “personal brand” by communicating their research and other related subjects [ 86 ]. Additionally, social media provide an avenue through which scientists can communicate to the public, which, although not new, is a more common and more requested pursuit for researchers today [ 87 – 90 ]. However, research shows that scientists utilizing social media are mainly sharing research within their own fields, with outreach to the wider public remaining a lower priority [ 75 – 77 , 79 ]. Some scientists also over-emphasize the importance of blogs as a tool for communicating with public audiences; blogs were previously thought to be useful for encouraging dialogues with citizens, but in practice have not been widely successful in reaching non-scientific audiences [ 79 , 91 ].

As illustrated above, science communicators have had difficulty in engaging citizens in two-way conversations on social media, which has led to calls for more innovative/inventive strategies to engage citizens with research, predominantly on subjects linked to important public policy issues [e.g., 92 ]. Furthermore, social media communication strategies often vary among communicators, including individuals and organizations, which affect whether communication is effective [e.g., 69 , 93 ].

This study investigated strategies to engage people with scientific and policy information on social media. Research indicates that social media practices can affect how audience members engage with posts shared by individual and organization communicators [ 31 ]. Therefore, the first research question addressed by this study is:

RQ1: How do individual and NGO communicators approach sharing scientific and policy information on social media, and what particular strategies do they apply in their activity to engage with their audiences?

Furthermore, science communicators have typically struggled to encourage conversations on social media, despite evidence of two-way conversations being more effective for information sharing than one-way transmission [ 32 , 33 , 49 , 51 , 52 ]. Therefore, the second research question addressed by this study is:

RQ2: Do particular social media strategies encourage two-way conversations between science communicators and online audiences, and what characteristics of the strategies encourage communicators and audiences to participate in two-way conversations?

The goal of this research was to identify communication practices that encourage two-way conversations between communicators and citizens on social media. If particular techniques are more engaging, they could be adopted or prioritized by communicators to improve how scientific and policy information is shared on social media, and ultimately enable citizens to participate in decision-making processes.

To address the research questions, the activity of four scientists acting as recognized science communicators using individual Twitter and Instagram accounts and the activity of three environmental non-governmental organizations (eNGOs) using organization Twitter and Instagram accounts to share scientific and policy information were studied. This number of communicators was selected to consider the research questions in a detailed, qualitatively data-rich manner (consistent with calls for such studies; [e.g., 24 ]) rather than be representative of all scientists and eNGOs communicating on social media. This study was conducted with established qualitative research methods appropriate for the sample size of communicators and volume and types of data collected [e.g., 94 ]. This research included: 1) an analysis of public Twitter and Instagram data of each of the seven account holders to identify practices implemented by communicators and resulting follower engagement in two-way conversations; 2) interviews with the individual and eNGO communicators to determine their social media strategies; 3) a survey of audience members involved in two-way conversations to determine why they participate in conversations on social media; and 4) an audience “biography” analysis to determine whether the communicators are engaging a scientific, non-scientific, or mixed audience on social media ( Fig 1 ). Following collection, the aggregated social media data were triangulated to develop thorough understanding of social media strategies used by the communicators.

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https://doi.org/10.1371/journal.pone.0241972.g001

Ethics approval for this study was obtained in the ethics review process established by the Social Sciences and Humanities Research Ethics Board at Dalhousie University. As required by the ethics approval, informed consent was obtained from the participants prior to the interviews and the survey. The social media data collection complied with the Terms of Service for both Twitter and Instagram. Twitter was selected for this study because it is actively used for science communication and has been studied to a greater extent than other platforms [ 35 , 75 – 78 ]. Instagram was selected because it is a newer platform, and fewer studies on the potential of Instagram as a science communication tool have been completed to date [ 35 , 78 ]. Studying usage of the two platforms, which offer different features, allowed determining whether the communicators were consistent in their application of social media strategies.

Account identification

Following the requirements of ethics approval, all of the participants were treated anonymously. The four individual scientists are located in four countries in North America and Europe. These scientists were chosen from The SciCommunity, an Instagram community that uses social media to make science, technology, engineering, arts, and mathematics more accessible ( instagram.com/thescicommunity ). The individual communicators were selected based on the order in which they joined the community. Beginning with the earliest community members (i.e., most established communicators), scientists who use personal Twitter and Instagram accounts to communicate primarily in English frequently each week, with accumulated 10,000 followers or more (Twitter and Instagram combined), were invited to participate in the study. Invitations were extended until four communicators agreed to participate in the study. The three eNGOs, also with many thousands of followers, were selected for their focus on sharing environmental information on Twitter and Instagram regularly each week, and for the scale of the organization (one local, one national, and one international). Invitations were extended to eNGOs that met the criteria until three agreed to participate in the study, Environmental NGOs were studied due to their growing role as science communicators to diverse audiences [ 63 , 95 ].

Social media data collection and coding

Publicly available Twitter and Instagram data posted by the seven communicators were collected for four weeks from July 30 to August 26, 2018, including all Twitter posts (TRPs), Instagram posts (IGPs), Instagram stories (IGSs), and all associated TRP and IGP comments. As this study followed a largely qualitative approach to investigate the social media practices of the communicators, one month was judged to be sufficient for analysis and triangulation with the interviews. During the interviews (see below), communicators were asked to focus their responses on their most recent social media activity. Twitter posts were collected once per day using the desktop version ( twitter.com ) one week after they were posted to allow time for audience engagement (from August 6 to September 2, 2018). A screenshot of the TRPs recorded the date/time of posting, captured images, and preserved a “snapshot” of the content and engagement. In the case of multiple Twitter posts together (i.e., a thread), the posts within a thread were captured and treated as a single post, unless posts occurred over multiple days.

Instagram posts were collected from the desktop version ( instagram.com ) in the same manner as TRPs. Instagram stories were collected twice daily to ensure none were missed (as stories expire after 24 hours). Screen capture software was used to record the video and audio associated with each IGS post. Each set of stories was saved as a video file and the stories were separated into threads based on the time between posting and topic continuity. Engagement data from IGSs are not public and were not captured.

The Twitter and Instagram data were organized in spreadsheets for statistical analysis in Rstudio version 1.1.456. For the TRPs, five spreadsheet files were created: original content, comments, handles, names, and reply type (response from the original communicator vs. a secondary social media user). The content files contained two columns—post caption data, and hashtag data—with each row representing a unique post. The other files were organized similarly, with each row containing data on either comments, handles, names, or reply types associated with a unique post. This process was used for IGPs, but only for original content, comments, and handles were created, as data for names and reply type are not recorded within Instagram posts. Each TRP, IGP, and IGS was categorized for the content characteristics [ S1 Table ] using codes based on topics listed as central to the goals of organizations, and the Instagram description for The SciCommunity. Because the Instagram story data were recorded in audio/visual formats, rather than text, the IGSs were only subjected to content coding. In total, 840 social media posts and 1399 comments were collected and analyzed.

Text analysis

The Twitter and Instagram post captions were subjected to text analysis using Linguistic Inquiry and Word Count 2015 (LIWC2015) software, which was used to identify the percentage of personal pronouns used in social media posts by the communicators, as such pronouns can affect how interactions between communicators and their audiences are perceived [ 96 ]. LIWC has been validated and used in numerous published research studies [ 75 , 97 ]. English and non-special character data in the text captions posted by each communicator were analyzed as a single dataset, aided by Excel. The analysis was conducted separately for the Twitter and Instagram data for each communicator. Individual and eNGO scores were aggregated, as both communicator groups were analyzed under the same conditions.

Interview data collection and analysis

The owners or representatives of the seven accounts were invited via email to participate in semi-structured interviews and to maintain anonymity were randomly assigned a code (e.g., IND1 for an individual scientist or ORG1 for an eNGO). The interview questions were designed to investigate how the communicators viewed their use of social media generally, along with their goals/objectives, their posting strategies, and their participation in social media conversations. The interviews, conducted by phone or Skype, were audio recorded. The interviews were transcribed verbatim and subjected to three rounds of coding, following established analysis processes [ 98 – 100 ], to draw out the themes from the textual data: an initial round to determine specific codes for each relevant interview response, a second round to create broader grouping of associated codes into categories, and a final round to restructure categories into overarching themes of all interviews. In the initial round, coding was conducted by one researcher, followed by a second researcher. The coding was compared and where discrepancies occurred, the researchers discussed the variations and resolved the differences. In subsequent rounds as the themes were drawn from the underlying coding, the second researcher reviewed the theme extraction to ensure consistency of application.

Survey data collection and analysis

An online survey, open from September 10 to October 31, 2018, was administered using Opinio software to query engaged users about their participation in two-way social media conversations. Individuals who posted English comments in two-way conversations on Twitter or Instagram posts of each of the accounts were invited to complete the survey. The participants were invited if they were involved in a conversation with a) one of the communicators in the study, or b) another user who commented on a communicator post. A two-way conversation was defined as a comment that received at least one response, with both the commenter and respondent invited to complete the survey. Accounts that were deleted or changed to a different “handle” by users before invitations were sent out, accounts that did not belong to individuals, accounts that were obvious trolls/bots (based on their social media profile and/or comments), and the seven accounts of the individual scientists and eNGOs in the study were excluded. A total of 425 conversationalists were invited to participate in the survey via either Twitter or Instagram (i.e., the platform in which a conversation occurred) using a unique comment that tagged the individual in a Twitter or Instagram post and asked to follow a link that directed them to a webpage containing the survey link. When users conducted conversations on posts of more than one of the accounts in the study, random selection was used to decide which account the user was contacted about. The participants were treated anonymously and limited to completing the survey once. The quantitative data were subjected to descriptive statistical analysis, and the free text responses were coded for content themes.

Audience analysis

The Twitter and Instagram biographies of the individuals invited to complete the survey were analyzed statistically with the aid of Rstudio version 1.1.456 to determine if they self-identified as scientists on social media. The individuals were classified as scientists if their biography mentioned science or science disciplines (e.g., neuroscientist, biochemistry), or if their social media profile pictures clearly depicted them as scientists.

Because the aim of this study was to investigate the relationship between communication techniques and audience engagement, particularly two-way conversations across Twitter and Instagram, analysis of the activity data from the two social media platforms, the interviews, and the survey text responses and demographic information were integrated for each communicator in the presentation of the results. This approach triangulates each communicator’s social media practices (both their views about their strategies and actual practices) with audience engagement, while highlighting similarities and differences in the strategies and engagement between each communicator and as either an individual communicator or eNGO. Because this study connects the application of strategies and resulting engagement throughout the social media activity of the communicators, social media data were analyzed in aggregate (i.e., strategies and engagement across all posts), rather than on a post-by-post basis.

Three strategy filters

The interviews and the Twitter and Instagram data show that the two communicator groups utilize three types of “filters” to guide their posting activity. First, the seven communicators operate within implicitly accepted social practices on each platform (i.e., platform conventions). Second, the two communicator groups apply specific activity strategies related to posting frequency and type of media used in posts. Third, the seven communicators implement interpersonal communication strategies in their posts. These three filters are implemented in a hierarchical manner, that is, the activity strategies are applied according to platform conventions, and the interpersonal strategies are applied in accordance with both the activity strategies and platform conventions. Interpersonal communication and strategies emerged as important characteristics of the communicators’ social media activity. Interpersonal communication has been the focus of extensive research [ 101 – 104 ]. The succinct definition by Braithwaite, Schrodt, & Carr [ 105 ], “interpersonal communication is the production and processing of verbal and nonverbal messages between two or a few persons,” is pertinent in this study as this definition accounts for communication centred on individuals, focused on interactions involving exchange of messages, and on development of relationships between the participants. As is shown below, the strategies that communicators implemented to promote interpersonal communication gave attention to one or more of these aspects.

Platform conventions

The interviews with the seven communicators show that accepted social media conventions play an important role in dictating the techniques applied by them, as they recognize that adherence to the common platform practices that have emerged over time will ensure their posts remain consistent with the expectations of social media users. The communicators expressed similar views of how they plan and implement strategies based on the platform conventions. For example, all of the communicators noted that Twitter tends to attract a more educated and/or issue-cognizant audience seeking news-centric information, and that Instagram draws a larger general/non-scientific audience interested in more personal multimedia posts, and therefore the seven communicators post accordingly to meet audience expectations (e.g., “You can share photos on Twitter, but it’s more visible and accessible on Instagram” (IND 4 interview)). Additional strategies applied by the communicators (discussed below), are implemented in compliance with implicit platform conventions.

Activity strategies

The individual and eNGO communicators implement particular strategies related to post frequency, platform priority, and media type used in posts—hereafter referred to as activity strategies—although with some variability. The eNGOs strive to post at regularly scheduled intervals, while maintaining flexibility to react when necessary. For example, one eNGO representative stated: “[we’re] doing as much planning as possible, but trying to leave in the flexibility to react when there is a more timely or necessary content need” (ORG2 interview). This approach allows the eNGOs to present well-researched information that is backed by evidence, while still giving the organizations an opportunity to share topical content and participate in social media “conversations” regarding breaking news or unexpected events related to their work (e.g., an interesting animal encounter during field work). In practice, ORG1 and ORG3 post on social media about 20 times/week ( Fig 2 ). ORG2, however, posts on Twitter and Instagram much more frequently, at a rate of >120 times/week ( Fig 2 ), because it “seems to be the most effective” for encouraging engagement (ORG2 interview). The individual scientists post in a less scheduled manner than the eNGOs, mainly when they feel inspired to do so. IND3 and IND4 post at similar rates to ORG1 and ORG3 (about 20–25 times/week), but IND1 and IND2 less than 10 times/week ( Fig 2 ). The individual scientists indicated that frequency is not as important as quality. They typically share based on more mentally “dynamic” factors (e.g., creativity, curiosity, inspiration, interest), and consequently do not feel motivated to post at high frequencies, which the individuals find to be overexerting or time consuming. As one communicator said, “I’ve kind of come to the point where it’s best for me just to post when I like, when [it] suits me best” (IND4 interview). Although the individual scientists did not discuss whether posting at high frequencies is an effective engagement strategy (other than ensuring the time between posts is not excessive, e.g., weeks), they did mention that they believed that the excitement/passion they are able to convey based on inspiration can be quite engaging for their audience.

Colours indicate the platform distribution of Twitter posts (TRPs), Instagram stories (IGSs), and Instagram posts (IGPs).

https://doi.org/10.1371/journal.pone.0241972.g002

The communicators decide which platform they use based on a mix of platform affordances and level of engagement received. However, the eNGOs and individual scientists do not prioritize the same platforms, in regard to intended strategies, or how they are translated into practice. ORG2 prefers Instagram over Twitter, as Instagram is seen as more aligned with the organization’s overall goals: “our preference, or our top performing platform I should say, has been Instagram … it’s still at a point of very rapid growth and evolution in terms of the functions or things you can and can’t do on the particular platform. So that’s lent itself to being a top performer” (ORG2 interview). ORG1 and ORG3 do not have expressed platform preferences. Nevertheless, based on actual post frequency, all three of the eNGOs prioritize Twitter over Instagram, sharing most of their posts (67–76%) on Twitter ( Fig 2 ). For ORG2, this practice is not consistent with the stated platform preference noted during the interview. All three of the individual scientists said they prefer Instagram—especially IGSs. For example, IND3 emphasizes posting on Instagram because that is “where [my] biggest audience is,” while also noting the importance of functionality: “I love how many dimensions there are to using Instagram. You can do pictures, you can do posts, you can do videos and stories, you can live stream. It’s so … versatile in how you can use it that it’s been incredible as a creator” (IND3 interview). The actual post frequency corroborates the interview responses of the individual scientists, as 69–85% of all their social media posts were shared on Instagram, particularly IGSs, with 50–77% of all posts shared via IGSs ( Fig 2 ).

All of the communicators post text, images, and videos in accordance with platform conventions. The two groups of communicators use media types (text, images, and video) in a similar proportion of posts, but the individuals use text differently. Both the individuals and the eNGOs include text in all posts, images in the majority of posts (56–98%), and videos in a smaller fraction of posts (2–36%) ( Fig 3 ). However, on Instagram, where the character limit is 2200 for each post, the individuals post an average of 244 words/caption, whereas the eNGOs use fewer words (an average of 102 words/caption) ( Table 1 ). On Twitter, where the post length is more limited (280 characters), all communicators post a similar average of words/caption (28 for eNGOs and 30 for individuals) ( Table 1 ). In addition, none of the individual scientists use Twitter to share videos, whereas two of the three eNGOs do ( Fig 3 ).

Proportion of social media posts by individuals and eNGOs containing A) images, and B) videos/GIFs, July 30-August 26, 2018. Colours indicate the relative proportion of posts with images or videos/GIFs in the TRPs, IGSs, and IGPs.

https://doi.org/10.1371/journal.pone.0241972.g003

https://doi.org/10.1371/journal.pone.0241972.t001

Interpersonal strategies

The seven communicators all noted in their interview responses that they aim to integrate interpersonal strategies into their social media activities. Some of these strategies are non-conversational, resulting in no direct interactions between the communicators and audience members. Six of the communicators stated that humanizing social media content is important for establishing personal connections with audiences. To humanize their organizations the representatives of ORG1 and ORG3 stated they display images of scientists or other staff members in posts. As one eNGO representative said, “It’s good for people to get to know who… the researchers or advocates are behind each of the stories and who’s working on them and why. I think [that’s] useful for people… that human aspect is important, and… giving people a chance to get to know who’s behind the controls is a good thing” (ORG1 Interview). However, the ORG1 and ORG3 representatives also stated that posting selfies and humanizing their organizations is one of their biggest social media challenges, particularly as the organization staff are often not willing to be seen in social media photos/videos, and because the organizations employ multiple staff members to create content for social media (ORG1 and ORG3 Interviews). In practice, ORG1 and ORG3 include selfies in a small fraction of their posts (14% and 15% of posts respectively), whereas ORG2 does not post any selfies on social media ( Fig 4 ).

Colours indicate relative proportion of posts with selfies in the TRPs, IGSs, and IGPs.

https://doi.org/10.1371/journal.pone.0241972.g004

Selfies are a key means of humanizing the individual scientists since displaying their faces allows people to become comfortable with them. The individual scientists stated they use selfies to convey authenticity and to encourage/invite their audience to engage with them. As IND3 said, “I do try to be the most honest version of myself that I can display,” which “is important because it helps people to understand and also care about what you’re communicating” (IND3 interview). Similarly, IND2 noted: “that’s why I like to film in a selfie mode, because also it… puts a face on a scientist. People like to connect with other people” (IND2 interview). IND1 also expressed a similar view: “that’s one hundred percent to be human… even if you post a photo with your science, or with your code, or whatever… I think even in my facial expressions I try to make it about inviting people in” (IND1 interview). Selfie strategies are evident in the actual posting activity of the individual scientists, who collectively utilize selfies far more frequently than the eNGOs, incorporating selfies into more than 30% of posts ( Fig 4 ). Additionally, selfie-style videos are important for the individuals, who noted they speak directly to their camera to convey a sense of talking directly to their audiences. The individuals believe these videos are especially effective for communicating on a personal level and establishing communicator-audience relationships. For example, IND3 explained how selfie-style videos feel very authentic and conversational:

I think video content, especially… a selfie-style video… feels pretty intimate actually. It feels like you’re having a one-on-one conversation, and it really helps… to build relationships with the audience. Because it feels very personal to have someone speaking right to you via the phone in your hand. (IND3 interview)

Selfie-style videos are commonly implemented as a strategy by the individual scientists, as a substantial proportion of their video posts (38–67%) include selfie-style audio ( Fig 5 ). In contrast, the eNGO communicators rarely use selfie-style audio in their video posts (5–7%), generally opting for no audio at all, or music-based audio ( Fig 5 ).

*Two or no videos posted (IND2 and ORG1).

https://doi.org/10.1371/journal.pone.0241972.g005

In addition to practices to humanize their social media activity, the communicators used non-conversational interpersonal communication strategies linked to the social media topics of their posts. Educating audiences through social media is an important goal of the eNGOs, and they give particular attention to the manner in which education is conducted. They emphasize a two-way model, rather than a top-down approach where information only flows from communicator to audience. For example, ORG1 pointed out: “I don’t know if it’s ‘teaching’… We don't want to be talk ‘down-y’” (ORG1 interview). The eNGOs also try to balance “heavier” educational/scientific content with “lighter” topics—such as posts focused on funny/interesting animals—and they use metaphors to make science content more accessible for their audiences. Similarly, the eNGOs stated they aim to make the content fun and interactive by presenting compelling information and mixing in humour. In addition, the eNGOs aim to build trust with their audiences by ensuring all of their posts are backed by scientific evidence. Overall, the social media activity shows that the eNGO communicators post consistently on topic (only an average of 9% of eNGO posts were off-topic, i.e., not clearly linked to the organization’s goals or mission, Fig 6 ), deciding to include entertainment and humour in posts topically linked to the organization’s goals/mission.

Colours indicate the relative proportion of off-topic posts in the TRPs, IGSs, and IGPs.

https://doi.org/10.1371/journal.pone.0241972.g006

Similar to the eNGOs, the individual scientists exercise two-way communication practices to avoid talking down to their audiences and to balance the educational component of their social media activity with lighter content such as humour and entertainment. One individual emphasized this sentiment, describing the educational component as “teaching, but with an engagement model… helping people to engage with educational content” (IND3 interview). However, in contrast to the eNGOs, the individual scientists mainly balance the content by including personal social media topics—such as daily activities that might be unrelated to science—and expressed a clear intention to post personal content using IGSs. For example, IND1 discussed how posting personal content on IGSs helps to portray scientists as people, i.e., regular individuals who have interests outside of science:

I think that Instagram stories humanize [science] more than anything else. Just because they’re quick, they don’t have to be high quality… Sometimes [content is] not exciting enough to warrant a whole post on Instagram, but you know, people like seeing it on the stories. Because it’s a way for them to check in with me, and like, what I am doing between posts. (IND1 interview)

The individuals also focus on expressing emotions in their post topics, and try to authentically display themselves, and scientists more generally, as warm, kind people as opposed to strictly knowledge experts absent of approachable qualities. In addition to ensuring their posts are all evidence-based (a strategy emphasized by the eNGOs as well), the individual scientists work to establish personal connections with their audiences in order to build trust. In highlighting use of selfie-style videos, IND3 said, “Recording an off the cuff video just kind of… confers some level of honesty. Because it’s you just free stream talking as if in conversation. And so, I try not to overly produce anything. Because I want people to see… we’re just talking, this is not so serious. We’re just having conversations, let’s delve in” (IND3 interview). The social media data demonstrate that the individual scientists share a larger proportion of off-topic posts than eNGOs (an average of 32% of posts were off-topic), many of which are about everyday activities ( Fig 6 ). The text analysis of social media posts via LIWC shows that individual scientists also use more first person personal pronouns in their posts than the eNGO communicators; 3.4% and 5.1% of words in captions posted by the individuals on Twitter and Instagram respectively were first person pronouns ( Table 1 ). In comparison, the eNGOs used such pronouns less frequently (2.1% of words on Twitter, 1.5% of words on Instagram).

The seven communicators also implement interpersonal communication strategies via two-way conversations with their audiences. The eNGO communicators stated that they prioritize responding to audience comments on their posts, especially when people ask questions. The eNGOs also put calls to action (such as requests for audience members to sign petitions or join meetings) and/or questions in their posts, and endeavour to make their posts captivating, all designed to encourage audience members to participate in social media conversations. In addition, the eNGO communicators view two-way conversations as an opportunity to establish personal connections with their audiences and form communicator-audience relationships. For example, ORG2 said that “it’s difficult to build that relationship without having a conversation. So… enabling the opportunity to interact one-on-one with the individual… [is an occasion] to be able … to take that next step in that relationship” (ORG2 interview). Nonetheless, the eNGO communicators did not particularly feel they have been successful in forming communicator-audience relationships, as noted by ORG1: “I don’t feel like I have much of a personal relationship with the followers, no” (ORG1 interview). While the eNGO representatives stated that engaging with audience members was important, in practice, ORG1 and ORG2 respond to few, if any comments (responding to less than 1% of comments per post) ( Fig 7 ). Although ORG3 responds to about 8% of comments per post, it still does so much less frequently than all individuals (who responded to an average of 15–34% of comments per post).

Colours indicate the relative proportion of comments responded to on TRPs and IGPs. Numbers on top of bars indicate the total number of comments responded to during the study period.

https://doi.org/10.1371/journal.pone.0241972.g007

In the interviews, the four individual scientists also discussed interpersonal communication strategies via two-way conversations with their audiences. They prioritize responding to audience comments (particularly questions), put calls to action and/or questions in their social media posts to encourage a conversations, and strive to establish personal connections with their audiences and form communicator-audience relationships via two-way conversations. This view was obvious in a statement by IND3: “A lot of the time we’re just building relationships, we’re laughing. I’ll post something funny, and someone will reply… Further, it’s important for me to let people know that scientists do care about them… We care about individuals more than people realize… So it’s important for me to address people’s concerns, and talk with them, and share with them information that they’re curious about” (IND3 interview). In practice, the individual scientists respond to a substantially larger proportion of audience comments than the eNGOs (15–34% of comments per post ( Fig 7 )). The individual scientists also highlighted that they have been able to form communicator-audience relationships through their social media activity, as evidenced by a comment by IND4: “Yeah, [meeting up with an audience member in person for the first time] was great. It was weird in the fact that it wasn’t a complete stranger. So although it was the first time that you met them, you were talking to them like you had known them for ages” (IND4 interview). One individual scientist noted that although typical conversations on posts might be short, the conversations can extend beyond single posts once communicator-audience relationships are formed:

Oh my gosh, they’re ongoing. They’re very ongoing. There are many examples of people messaging me to ask for advice … and [they] almost always follow up. So I had one woman applying to a … program, and we actually even met in person because she happened to be visiting, and we exchanged some advice and conversation. And a year later she followed up and let me know she got into the program … and we had been chatting in the interim, but not so much. But many times people will follow up and let me know how it went, and say thank you, and say, “Oh I also learned this, you can tell people that next time” … So now we’ve turned a one-time interaction into a long-term resource, which I think is cool. (IND3 interview)

In contrast, the eNGO communicators noted during interviews their intention to build relationships with audience members through social media, but did not indicate that they had been successful in doing so.

Audience engagement on communicator posts

Triangulation of the social media and survey data was carried out to understand why audience members decided to engage with social media posts shared by the communicators. The individual scientists receive more conversational engagement than the eNGOs, that is, the individuals receive more and longer comments, and generate a larger number of direct interactions with unique conversationalists ( Table 2 ). The individuals receive 20–42 comments/post/10,000 followers on Instagram, and 0.8–60 comments/post/10,000 followers on Twitter whereas the organizations receive 1–4 comments/post/10,000 followers and almost no (0.05–0.4) comments/post/10,000 followers on Instagram and Twitter, respectively ( Table 2 ).

https://doi.org/10.1371/journal.pone.0241972.t002

Comments on the individual scientists’ posts ranged from 11–26 words in length on Instagram and 9–26 words on Twitter ( Table 2 ). In contrast, comments on the eNGO communicators’ posts ranged from 5–7 words on Instagram and 2–15 words on Twitter ( Table 2 ). Although the total number of unique conversationalists varied across the two groups and platforms ( Table 2 ), an average of 74% and 85% of unique users interacted directly with the individual communicators on their Twitter and Instagram posts, respectively (although IND1 on Twitter was far lower than the other individuals). An average of 30% of unique conversationalists interacted directly with the eNGO communicators on their Twitter posts, and an average of 23% did so on Instagram posts ( Table 2 ).

Although direct message data were not collected (this information is not public in either Twitter or Instagram), all of the communicators indicated during the interviews that direct message engagement does not occur more frequently than comment engagement. Furthermore, although the eNGO communicators engage a majority non-scientific audience (0–22% of conversationalists across Instagram and Twitter were identified as scientific users), the individual scientists reach a mixed audience consisting of both scientific and non-scientific users–particularly on Instagram–with 42–67% of conversationalists identified as scientific users on Instagram, and 44–100% identified as scientific users on Twitter ( Table 2 ). While mixed, scientists constitute a large proportion of the audience of the individual communicators.

The survey of conversationalists yielded a response rate of 10% (45 out of 425 invited to complete the survey). Most of the survey respondents were engaged on posts of the individual scientists (five on Twitter and 33 on Instagram), and seven were engaged on posts of the eNGO communicators (all from Instagram). The majority (62%) of respondents who identified their age were between 19–33 years old, with a smaller proportion (16%) aged 5–18 and 34–49 combined ( Table 3 ). Only two of the survey participants were 50 or above. Most of the survey respondents who revealed their gender identified as female (82%) ( Table 3 ). The respondents were also highly educated and science-associated overall: 83% of respondents had some level of post-secondary education, and 80% consider themselves part of the scientific community ( Table 3 ). Although the majority of survey participants were well educated and science-associated, many users who participated in conversations on the posts of the science communicators were not scientists, especially those engaged with eNGO posts ( Table 2 ).

https://doi.org/10.1371/journal.pone.0241972.t003

Some survey participants provided open text responses that explained why they engage in conversations on posts of the communicators, frequently expressing personal sentiments (emotional connections to the communicator and/or their posts) in their responses, rather than focusing on education or links to science. Those who prefer to engage in conversations on Twitter do so due to its short message length and focus on news/relevant information ( Table 4 ). The participants who expressed a preference for Instagram drew attention to its visual nature, its communication features, and its ease of use/functionality ( Table 4 ). Regardless of platform preference, the most cited reasons for using Twitter related to the participants’ work and their seeking news/information. In contrast, the participants use Instagram because of the platform’s visual nature, and for personal reasons such as self-expression, relationship-building, and connecting with friends/family ( Table 5 ). Personal sentiments also emerged when the respondents wrote about their motivation for following particular accounts. Although they follow the communicators to receive new information, many also do so because they find the communicators (or the content) to be relatable ( Table 5 ).

https://doi.org/10.1371/journal.pone.0241972.t004

https://doi.org/10.1371/journal.pone.0241972.t005

A theme that emerged from all survey responses was the participants’ sense of personal connection with the communicators, which encouraged participation in conversations, particularly on Instagram, which the participants viewed as a more personal social media platform compared to Twitter. For example, one participant stated: “it seems personal and engaging (photos and captions) but without the threat of things getting out of hand or out of context like on Twitter.” The survey respondents also noted that Instagram is quite conducive to communication, illustrated by the participant who stated: “I’m most active on Instagram and it’s easy to make and respond to comments, posts, and stories.” When the respondents commented about their decisions to engage with the communicators, many (12 out of 19) did so in terms of personal connections, perceived authenticity of the communicator, and feeling that they knew the owner of the account ( Table 5 ). For example, one wrote, “for me it is easier to contact a person instead of an organization with 'unknown faces' behind it.” Another respondent described a sense of comfort in interacting with organizations that are comprised of known individuals, “I use social media for work so I know there are ‘individuals’ behind the organization… However if I didn’t know the organisation, then I would be less likely to reply.”

When queried about establishing relationships with the communicators, 24 respondents added explanations, and 13—both those that do and do not feel that they have formed relationships with the communicator—commented specifically about two-way conversations. One did not feel an opportunity to form a relationship was presented, because direct interactions had only occurred with other users, not the communicator: “I don't think [the communicator has] ever responded to anything I've said on their post, responded to one of my posts, or anything of the like. It's impossible to feel any link if it's not reciprocal.” In contrast, those who formed relationships emphasized the dialogic interactions: “we have commented back and forth to each other as well as [direct messaged] in the past!” Two others expressed similar comments: “we talk in private as well as I do with my friends”; and: “I often message [them] if I need to know anything about being in academia, because I am new to it and [they are] really helpful.” One respondent also stressed that the way posts are presented on social media is crucial, and can result in a relationship-type connection in the absence of direct interactions with the communicator:

We don’t talk, but their welcoming demeanor and friendliness makes learning science personal. It feels like engaging with a friend. Their method of communication makes science a more fun and accessible conversation. You feel like you are involved, and you can always put forth your input without judgement—something that is super important because science can appear condescending to a lot of people. It’s constant learning and that’s all that matters.

Recognizing that social media provide a means of two-way interactions—which research suggests are crucial for effective communication [ 33 , 34 ]—individual scientists and NGOs are increasingly using social media platforms to communicate with their audiences and promote science literacy [ 46 , 47 , 68 , 75 , 106 ]. However, individual and NGO communicators have had difficulty fostering two-way exchanges with their audiences on social media [ 33 , 106 ]. With evidence that the way in which communicators use social media plays an important role in determining audience engagement [e.g., 31 ], this study investigated how individual and NGO communicators approach sharing scientific information on social media, and the strategies they apply to engage with their audiences (RQ1).

The individual and eNGO communicators in this study implement three strategy “filters” in a hierarchical manner to guide their posting activity. First, both communicator groups follow implicit platform conventions when sharing posts on social media. All of the communicators follow a similar approach to ensure their posts are consistent with audience expectations, for example, focusing on more news-centric content in Twitter posts (TRPs), and more visually interesting content in Instagram posts (IGPs).

Second, both of the communicator groups are intentional in how often they post on the social media platforms, as well as in the types of media they use in posts. This activity “filter” is applied differently between the communicator groups. For example, the eNGOs implement a more scheduled approach, typically posting frequently, at regular intervals, and mainly on Twitter. In contrast, the individual communicators are more flexible in how often they post, and share information mainly via Instagram, particularly Instagram stories (IGSs). However, the activity strategies applied by the communicators do not link directly with conversational engagement on their social media posts. When comparing proportional engagement between the communicators (normalizing engagement to the number of followers for each communicator), ORG2—which posts far more frequently than the other communicators—receives fewer comments than the other communicators, and is in conversations with fewer unique users. IND1 and IND2 post less frequently than the other communicators, but they do not receive lower engagement with regard to user comments or unique conversationalists. A link between media type used (frequency of text, images, videos) and conversational engagement is also not obvious. Furthermore, a connection between the platform given priority in practice (i.e., the platform posted to most frequently) and conversational engagement is not evident, as all of the eNGOs receive more engagement on IGPs than TRPs despite posting more frequently on Twitter than Instagram.

The data in this study show that the implementation of interpersonal social media strategies by the communicators (i.e., the third strategy “filter”) encourages conversational engagement (RQ2). The next section discusses the characteristics of interpersonal strategies that encourage communicators and audiences to participate in two-way conversations (RQ2).

Interpersonal communication strategies and social media engagement

A variety of interpersonal communication strategies have been demonstrated to affect social media engagement [ 62 ], many of which are used by both the individual and eNGO communicators. For example, both the individuals and eNGOs actively invite people to participate in conversations on their posts, which is important because this approach encourages engagement, an opportunity that would otherwise be missed [ 25 , 62 , 107 ]. However, the individual scientists more comprehensively implement interpersonal communication strategies. First, the individuals post selfies and selfie-style videos more frequently than the eNGOs. This difference is noteworthy for engagement, as social media users are more willing to comment on posts by communicators whom they know, and more likely to initiate conversations with communicators who are familiar to them [ 26 , 29 , 69 ]. Furthermore, previous research shows that speaking directly to social media audiences through the camera—as is common practice for the individuals in selfie-style videos—can personally connect communicators with audience members and help to build trust and establish communicator-audience relationships, even in the absence of direct communicator-user interactions [ 27 , 84 , 108 , 109 ]. In addition, research on interpersonal communication has shown that this form of communication entails establishing relationships among the participants [ 105 ]. The results of this study support the link between selfie-style posts, two-way conversations, and communicator-audience relationships, as the individual scientists receive more engagement than eNGOs overall, and successfully formed relationships with their audiences, even in the absence of direct interaction (as corroborated by the survey responses). The frequent use of selfie-style image and video posts appears to be an effective strategy to build trust, establish communicator-audience relationships, and stimulate discussions of science on social media, which science communicators could implement to encourage effective science communication.

The expression of interpersonal sentiments in posts is also important for social media engagement, as recent research suggests that content characteristics affect engagement. For example, when users see social media posts similar in nature to their own, they are better able to connect with the content on a personal level and engage with it [ 28 , 30 ]. Although both communicator groups discussed strategies to make their social media content more relatable, the individual scientists receive more engagement in terms of two-way conversations than eNGOs overall, which may be because the former choose to focus on posting personally-relatable content. When the individual scientists post off-topic content such as day-to-day activities and frequently use first person pronouns in posts, they create relatable, shared stories that are thought to be key for audience engagement [ 26 , 110 ]. In fact, posts with a personal sentiment or message (including those without any science content) can surpass scientific posts in terms of engagement, even on science-focused accounts [ 107 ]. A link between engagement and personal content was evident in the survey responses, which showed users choose to follow communicators with whom they can relate. The results of this study suggest that the use of personal and relatable social media content promotes more two-way interactions in social media with science communicators than would otherwise occur.

Previous studies show that using two-way conversations to form communicator-audience relationships is important for social media engagement. Two-way conversations can result in personal connections between users and organizations, and cultivate positive organization-public relationships, which are crucial because organizations often have difficulty in retaining engaged users on social media [ 62 , 111 – 113 ]. However, the means through which relationships are formed between organizations and users on social media goes beyond direct interactions, as research shows that a significant number of users are influenced by the interactions they see online. When communicators engage with an individual, they are indirectly affecting relationship perceptions for others who observe the interaction, even when no direct communication takes place with the latter [ 114 ]. Additionally, the survey responses demonstrate that communicators are capable of establishing relationships with audience members through the use of personal sentiments even in the absence of direct interactions. Therefore, because the eNGOs currently respond to a smaller proportion of audience comments compared with the individual scientists, the eNGOs engage in fewer two-way conversations and therefore may be more limited in their ability to form communicator-audience relationships than individuals. This outcome is supported by this study: two-way conversations between individual communicators and audience members resulted in the establishment of communicator-audience relationships, whereas the eNGOs communicators were less successful in forming relationships with their audiences. Furthermore, because more conversations can result when communicators form relationships with their audiences (as discussed above), two-way conversations and communicator-audience relationships appear to be mutually reinforcing. Consequently, focusing on responding to audience comments to form communicator-audience relationships is likely an effective strategy to create sustained social media engagement between science communicators and their audiences. One of the individual scientists emphasized that conversations are not limited to individual posts; instead, when communicators establish relationships with their audiences, the relationships allow conversations to extend beyond a discrete instance, and into a larger, ongoing conversation. Therefore, science communicators will benefit by being responsive to social media comments and working to establish communicator-audience relationships in order to facilitate longer-term, ongoing conversations about science [ 115 ].

Non-scientific audience engagement

Both the individuals and the eNGOs stated that they specifically target non-scientific audiences with their social media activity (although the communicators do not limit their audiences to non-scientific users alone). In the interviews, all seven communicators pointed out that they generally use Instagram to reach non-scientific audiences, as they feel the platform attracts a larger population of non-scientific users than Twitter. Studies have shown, however, that the educational distribution of users on Twitter and Instagram is relatively similar [ 116 , 117 ]. The apparent mismatch between the perception of the communicators and subscriber base of the two platforms may be due to the topics of focus by the communicators on social media and the audiences that they have built. To date, scientists have typically been heavier users of Twitter than Instagram, and because the communicators post an abundance of science-based content [ 78 , 79 ], they may attract more scientists via Twitter than Instagram. Furthermore, education level does not necessarily equate to science literacy. In this study, all of the communicators except IND1 appear to engage a larger proportion of scientific users in conversations on Twitter than on Instagram. Moreover, a higher proportion of users in conversations on posts by the eNGOs are non-scientific compared to the individual scientist communicators. This result is likely a consequence of the differences in target audiences, topics, and social media goals among the communicators indicated during interviews. Nonetheless, the individual scientists engage a mixed (scientific and non-scientific) audience on social media, particularly on Instagram. Therefore, as this study shows, focusing on Instagram as a platform to reach non-scientific audiences for science conversations could be an important science communication strategy.

Interpersonal communication afforded through Instagram

Determining the extent to which Instagram fosters social media engagement is another informative outcome in this study. Not only did a greater number of two-way conversations take place on Instagram than Twitter for nearly all of the communicators (including the eNGOs that do not prioritize the platform in practice), Instagram was favoured by the communicators and survey participants for conversation-related uses overall, particularly illustrated by their understanding of accepted social media practices. The visual, informal, multi-functional, cordial, and multimedia-focused nature of Instagram (both posts and stories) contributes to it being a more conversational platform than Twitter. Science communicators could capitalize on this functionality of Instagram to encourage more conversations and informative two-way science communication with diverse audiences.

Implications

This study is especially informative for understanding characteristics of science communication on social media, and could contribute to dialogic theory on science communication more broadly, as the results highlight factors that play an important role in fostering two-way exchanges [ 62 , 106 , 118 ]. The use of more formal methods typical of traditional science communication practices, i.e., through transfer of publications (data and information in various forms, e.g., peer-reviewed research papers) [ 119 – 122 ], often results in a transmission pathway, where conversations are limited between communicators and their audiences ( Fig 8 ). In contrast, the implementation of interpersonal strategies by science communicators promotes the formation of communicator-audience relationships and encourages audiences to participate in more two-way conversations, resulting in positive feedback effect ( Fig 8 ). Crucially, because the interpersonal communication practices observed in this study mainly relate to how content is shared rather than what information is shared or who it is shared with, such strategies are applicable to a wide diversity of subjects and audiences. Therefore, science communicators of all types (individual scientists, organizations, government agencies, etc.) can communicate interpersonally with citizens about a variety of scientific topics for which research information is relevant to make policy decisions, promoting citizens to be more scientifically engaged in environmental, health, and other issues.

Formal strategies are not sufficient to establish a relationship between audience and communicator, resulting solely in a transmission pathway. Interpersonal strategies act as enablers to information flow, resulting in communicator-audience relationships, which promote two-way conversations sustained over time.

https://doi.org/10.1371/journal.pone.0241972.g008

For organizations such as eNGOs that are communicating with large non-scientific audiences, the potential to engage citizens in the science of environmental issues through interpersonal strategies is high. Importantly, because organizations do not operate in the same manner as individual scientists, they may be more limited in their ability to adopt interpersonal communications (for example, organizations are staffed by multiple individuals, and/or may be hesitant to share off-topic content or use first person pronouns due to organization culture) [ 123 , 124 ]. Furthermore, organizations face particular challenges and risks when using social media, such as losing control of the narrative of messages or being portrayed as less authoritative, which are not eliminated with the implementation of interpersonal strategies. In such cases, organizations could develop specific guidelines for implementing interpersonal communication into their social media activities in a manner consistent with higher-level organization practices. Nonetheless, because the eNGOs in this study share many goals with the individual scientists (such as encouraging two-way science conversations), eNGOs could apply interpersonal communication strategies—through a “spokesperson,” for example—and promote improved scientific literacy in their audiences on environmental issues that the organizations are engaged with.

Although this research investigated science communication on social media, the interpersonal strategies observed to promote conversations with citizens are applicable to all science communicators in diverse environments. Science communicators working to engage their audiences with environmental research information can apply interpersonal techniques offline as well as online. For example, communicators could utilize interpersonal communication strategies to establish relationships with relevant stakeholder groups involved in participatory policy processes and gain a better understanding of stakeholder concerns, ultimately leading to greater cooperation and more effective management decisions that are inclusive of stakeholder values [ 115 ].

Limitations and future work

The sample size of communicator participants was selected to examine the research question in a detailed and qualitatively data-rich manner rather than be representative of all scientists and eNGOs communicating on social media; nonetheless, increasing the number of communicator participants could reveal whether the conclusions of this study hold across a broader group of communicators and their audiences. Additionally, a longer period of study than was the source of data in this research, would provide further insights into communication patterns, such as how social media behaviours may be changing over time, regarding platform functionality and the way in which users employ social media tools (for example, a new feature called Instagram TV was instituted while this research was in progress). The ways in which social media research is conducted may also be required to change over time as the relationship between researchers and platform providers evolves and data access shifts [ 125 , 126 ]. The study was focused on Twitter and Instagram; future work could include other popular social media platforms such as Facebook and YouTube to advance understanding of the effects of interpersonal communication on engagement across more platforms. The communicator participants in this study share slightly different information on social media (i.e., the individual scientists focused mainly on a range of science topics, whereas the eNGOs included more politics and advocacy, with science aspects), which could affect audience engagement. Further research could compare individual scientists and eNGOs focusing on a single science topic to identify any effect of content topic on audience engagement.

The demographic concentration of the survey participants tended toward younger, highly educated respondents. Future work could use sampling techniques to evaluate whether links exist between demographic characteristics and the choice to participate in social media conversations, as well as survey a larger number of audience members to draw broader representative conclusions. Furthermore, conversation quality and message framing were not measured to determine the extent to which social media conversations were scientifically meaningful and learning-oriented, or how messages were framed. Additional investigation into social media as tools to facilitate a participatory model of communication could advance understanding of conversation quality. Evidence from the survey in this study suggests that communicators are positively influencing audience behaviour. For example, 44% of the survey participants (n = 41) feel inspired by communicator posts to make behaviour changes in regard to the natural environment. Therefore, future research that focused on conversation quality could provide additional insight into the effectiveness of science communication to influence behavior. Determining deeper understanding of the extent to which communicators are reaching non-scientific audiences, and how communicator-audience networks are structured and operate, could be obtained through studies that investigate how to measure the level of effectiveness of conversations in communicator/audience interactions, the role of communicator/audience networks, and the presence of lurkers in such networks.

Conclusions

A social media presence by itself is not sufficient for successful communication; how social media tools are used to encourage two-way conversations is an important determinant of engagement [ 25 , 118 ]. Both the individual and eNGO communicator groups in this study share similar communication goals and conveyed strong awareness of strategies known to be effective for science communication (such as two-way conversations). The two communicator groups apply interpersonal communication strategies differently in their social media activity. One difference that emerged is their overall application of interpersonal communication strategies. The individual scientists particularly focus on making themselves known and relatable communicators throughout their social media activity, and on establishing relationships with their audiences. In practice, the individuals achieve this outcome by posting more selfies (images and videos), posting more off-topic content, responding to more comments, and using more personal pronoun-prominent language than the eNGOs achieved. The individual scientists also prioritize Instagram over Twitter (and particularly Instagram stories), which more readily supports the implementation of interpersonal communication strategies than Twitter. This emphasis by the individual scientists on interpersonal communication promotes the formation of communicator-audience relationships, encouraging more two-way conversations and generating greater numbers of opportunities to form relationships with their audiences than the eNGOs. In other words, the results of this study show that a combination of interpersonal communication strategies, and their application throughout the social media activity of science communicators via the features of the social media platforms, especially in Instagram, play an important role in determining audience participation in two-way conversations, and ultimately affect how audience members engage with communicators over time.

Supporting information

S1 table. codes and definitions used to characterize twitter post, instagram post, and instagram story content..

https://doi.org/10.1371/journal.pone.0241972.s001

Acknowledgments

The individual scientists, eNGOs, and survey participants who participated in this study are acknowledged with thanks. Peter Wells, International Ocean Institute Canada, and Suzuette Soomai, Canada Department of Fisheries and Oceans, provided helpful insights. This paper benefitted from the detailed assessment by the PLOS ONE anonymous reviewers.

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200+ Google Scholar Research Topics: Strategies & Example

Academic research is all about learning new stuff and finding answers to questions. Whether you’re a student, teacher, or just someone curious, Google Scholar is like a super helpful friend for your research adventures. 

In this guide, we’ll explore how Google Scholar can make your research journey easier and more exciting. Moreover, we will check the Google Scholar Research Topics. So, let’s dive in!

What Would Be Search Strategies For Google Scholar?

Google Scholar’s search capabilities go far beyond the basic search bar. To unlock its full potential, it’s crucial to understand advanced search techniques, Boolean operators, and filters. Here are some strategies to consider:

Advanced Search Techniques

Google Scholar offers an advanced search feature that enables you to refine your queries. You can use this feature to narrow down results by specific authors, journals, publication dates, and more. It’s a powerful way to find precisely what you’re looking for.

Boolean Operators

Employing Boolean operators like “AND,” “OR,” and “NOT” can help you create complex search queries. For instance, combining “climate change” AND “policy” can yield research papers that specifically address the intersection of these two topics.

Filters and Operators

Utilizing filters and operators, such as the citation count, can help you identify the most influential and highly cited research in your field. This can be especially useful for locating seminal papers.

80+ Google Scholar Research Topics: Subject Wise Topics

• The Impact of Climate Change on Biodiversity
• Quantum Computing: Current Developments and Challenges
• Nanotechnology Applications in Medicine
• The Role of AI in Drug Discovery
• Dark Matter and the Structure of the Universe
• Advancements in Gene Editing Technologies
• Renewable Energy Sources and Sustainable Solutions
• The Effects of Pollution on Aquatic Ecosystems
• Ethical Considerations in AI and Machine Learning
• Cybersecurity Threats and Mitigation Strategies
• Internet of Things (IoT) and its Impact on Daily Life
• Augmented Reality and Virtual Reality in Education
• Blockchain Technology and Its Applications Beyond Cryptocurrency
• 5G Technology and Its Potential for Transforming Communication
• Human-Computer Interaction and User Experience Design
• Robotics in Healthcare: Current Trends and Future Prospects
• Precision Medicine and Personalized Treatment Approaches
• Mental Health Stigma and Access to Care
• The Role of Gut Microbiota in Human Health
• Advances in Cancer Immunotherapy
• Telemedicine and Remote Patient Monitoring
• Health Disparities Among Vulnerable Populations
• Antibiotic Resistance: Causes and Solutions
• Aging and Neurodegenerative Diseases: Research Challenges

Social Sciences

• Social Media’s Influence on Political Behavior
• The Psychology of Social Networks and Online Communities
• Gender Inequality in the Workplace: Recent Developments
• The Impact of Immigration Policies on Social Cohesion
• Educational Inequality and Access to Quality Education
• Climate Change and Public Opinion: A Global Perspective
• Youth Activism and Social Change Movements
• Cultural Diversity and Identity in Contemporary Society
• Postcolonial Literature and Identity
• The Philosophy of Ethics and Morality
• Historical Preservation and Cultural Heritage
• Existentialism in Modern Literature and Philosophy
• Art as a Medium for Social Commentary
• The Influence of Ancient Philosophers on Contemporary Thought
• Folklore and Oral Traditions in Modern Society
• Human Rights and Literature in Global Contexts
• The Evolution of Digital Art and New Media
• Contemporary Dance and Its Exploration of Gender Roles
• Sound Art and its Impact on Auditory Perception
• Environmental Art and Sustainability Messages
• Film as a Reflection of Societal Values
• The Intersection of Technology and Visual Arts
• Street Art and Graffiti as Forms of Urban Expression
• Music Therapy and its Therapeutic Applications
• Quantum Entanglement and Communication
• Gravitational Waves and their Detection
• Superconductivity and Its Potential Applications
• Particle Physics: The Quest for Fundamental Particles
• Black Holes: Unveiling the Mysteries of the Universe
• Quantum Computing and Quantum Algorithms
• Dark Energy and the Fate of the Universe
• Advanced Materials for Energy Storage and Conversion
• Behavioral Economics and Decision-Making
• Income Inequality and Its Economic Consequences
• Economic Impact of Global Trade Agreements
• Financial Markets and Behavioral Biases
• Sustainable Economic Development Models
• Economic Resilience in the Face of Global Crises
• The Economics of Healthcare Systems
• Cryptocurrency and Its Implications for Monetary Policy
• Cognitive Neuroscience and Memory Processing
• Psychopathology and Innovative Treatment Approaches
• The Psychology of Social Media Addiction
• Positive Psychology and Well-Being Interventions
• Cross-Cultural Psychology and Cultural Norms
• Child Development and Early Childhood Education
• Emotional Intelligence and Workplace Success
• Psychology of Decision-Making in High-Stress Situations
• Historical Analysis of Revolutionary Movements
• Environmental History and the Impact of Human Activity
• Ancient Civilizations and Their Cultural Legacy
• History of Science and Technological Advancements
• The Role of Women in Historical Events
• Indigenous Histories and Narratives of Resistance
• World Wars and their Socioeconomic Consequences
• Historical Preservation and Museums as Educational Tools
• Postmodern Literature and Its Fragmented Narratives
• Transcultural Literature and Identity in Migration
• Science Fiction as a Reflection of Technological Progress
• Shakespearean Studies in Modern Contexts
• Contemporary Poetry and its Exploration of Language
• Graphic Novels as a Medium for Social Commentary
• Literature and Ecocriticism: Nature’s Role in Stories
• Dystopian Fiction and its Socio Political Themes

25+ Google Scholar Research Topics For Beginners

• Introduction to Google Scholar: An overview of what Google Scholar is and how to use it effectively for academic research.
• Research Basics: Exploring the fundamental principles of research, including formulating research questions and conducting literature reviews.
• Citing Sources: Understanding the importance of proper citation and how to cite sources using different citation styles like APA, MLA, or Chicago.
• Research Ethics: An introduction to ethical considerations in research, including plagiarism, informed consent, and data integrity.
• Using Keywords: Tips and techniques for selecting and using keywords effectively to improve search results.
• Finding Reliable Sources: Strategies for identifying reputable and peer-reviewed sources in Google Scholar’s search results.
• Creating Alerts: How to set up email alerts for specific research topics or authors to stay updated on the latest publications.
• Managing References: An introduction to reference management tools like Zotero or Mendeley for organizing and citing sources.
• Research Question Development: Guidance on formulating clear and focused research questions that drive your inquiry.
• Literature Review: Basics of conducting a literature review to summarize and analyze existing research on a particular topic.
• Primary vs. Secondary Sources: Understanding the difference between primary and secondary sources in academic research.
• Data Collection Methods: An overview of various methods for collecting research data, including surveys, interviews, and observations.
• Statistical Analysis: Introduction to basic statistical concepts and tools for analyzing research data.
• Research Presentation: Tips for creating effective presentations and posters to communicate research findings.
• Choosing a Research Topic: Strategies for selecting a research topic that aligns with your interests and goals.
• Research Design: Exploring different research design options, such as experimental, observational, or case study approaches.
• Data Visualization: Basics of creating visual representations of data, including graphs and charts.
• Qualitative Research Methods: An introduction to qualitative research approaches, including content analysis and thematic analysis.
• Quantitative Research Methods: An overview of quantitative research methods, including surveys and experiments.
• Writing a Research Paper: Steps and guidelines for structuring and writing a research paper, from the introduction to the conclusion.
• Peer Review Process: Understanding the peer review process and its role in ensuring the quality of research publications.
• Using Google Scholar Metrics: Exploring Google Scholar Metrics to assess the impact and visibility of research articles.
• Open Access Journals: Learning about open access journals and their role in making research more accessible.
• Research Funding: An introduction to sources of research funding, grants, and scholarships for beginners.
• Collaborative Research: Tips for collaborating with other researchers and forming research partnerships.

15+ Google Scholar Research Topics For Intermediate

• “The Impact of Artificial Intelligence on Healthcare Delivery: A Comprehensive Review”
• “Environmental Sustainability in Urban Planning: Analyzing Current Practices and Challenges”
• “The Role of Social Media in Shaping Political Discourse: A Comparative Analysis”
• “Exploring the Effects of Climate Change on Global Food Security: A Multi-Disciplinary Approach”
• “The Psychology of Online Learning: Factors Influencing Student Engagement and Performance”
• “Digital Marketing Strategies in E-commerce: An Analysis of Best Practices and Emerging Trends”
• “Cross-Cultural Communication in Global Business: Challenges and Strategies for Success”
• “The Neurobiology of Addiction: Insights into Treatment and Rehabilitation”
• “Impact Investing and Sustainable Finance: Evaluating Social and Environmental Outcomes”
• “The Evolution of Renewable Energy Technologies: Assessing Viability and Adoption”
• “Criminal Justice Reform: Evaluating the Effects of Restorative Justice Programs”
• “The Influence of Literature on Social Movements: A Comparative Study of Historical Contexts”
• “Cybersecurity Threats in the Internet of Things (IoT): Strategies for Protection and Resilience”
• “The Ethics of Artificial Intelligence: Addressing Bias and Accountability in AI Systems”
• “Post-pandemic Workforce Trends: Remote Work, Mental Health, and Organizational Adaptation”

10+ Google Scholar Research Topics For Advanced

• Quantum Computing Algorithms for Cryptography: Investigate advanced quantum computing algorithms and their implications for cryptography and data security.
• Neural Networks in Natural Language Processing: Explore cutting-edge techniques in neural network-based natural language processing and their applications in machine translation and sentiment analysis.
• Genome Editing and Ethical Considerations: Analyze the ethical challenges surrounding genome editing technologies like CRISPR-Cas9 and their potential impact on society.
• Advanced Data Mining Techniques for Healthcare: Research advanced data mining and machine learning methods for predicting disease outbreaks and improving patient outcomes in healthcare.
• Post-Quantum Cryptography: Investigate cryptographic methods designed to withstand attacks from quantum computers, which have the potential to break current encryption algorithms.
• Neurobiology of Consciousness: Delve into the intricacies of neurobiology to explore the nature of consciousness and its neural correlates.
• Quantum Machine Learning: Explore the intersection of quantum computing and machine learning to develop quantum-enhanced algorithms for solving complex problems.
• Artificial General Intelligence (AGI): Study the development of AGI systems, which possess human-level intelligence, and examine the ethical and societal implications of AGI.
• Advanced Materials for Renewable Energy: Investigate novel materials and nanotechnologies for enhancing the efficiency and sustainability of renewable energy sources like solar cells and batteries.
• Social Network Analysis in Cybersecurity: Analyze advanced techniques in social network analysis to detect and mitigate cybersecurity threats and attacks in complex online environments.

Tips and Guides: How To Search Google Scholar Research Topics

• Research Topic Selection: Discovering the right research topic is crucial. Google Scholar can assist you in identifying trending topics and gaps in existing literature.
• Literature Review: Conducting a thorough literature review is a fundamental step in research. Google Scholar’s vast database simplifies the process of finding relevant studies.
• Bibliographic References: Google Scholar generates citations in various citation styles, making it easier to compile your bibliography.
• Evaluating Sources: Not all sources are created equal. Google Scholar provides tools to assess the reliability and credibility of sources, ensuring you rely on trustworthy research.
• Academic Writing: Improve your academic writing skills by reading well-crafted research papers available on Google Scholar. Analyze their structure, style, and citation methods.

Example: How To Get Desired Google Scholar Research Topics?

Let’s take the example of researching the topic “Neural Networks in Natural Language Processing” using Google Scholar. I’ll provide a step-by-step guide and include a table to organize the information.

Step 1: Access Google Scholar

Go to Google Scholar using your web browser.

Step 2: Formulate Your Search Query

In the search bar, enter your research topic: “Neural Networks in Natural Language Processing.”

Step 3: Refine Your Search

To refine your search results, you can use various techniques:

Quotation Marks: To search for an exact phrase, put it in quotation marks. For example, “Neural Networks in Natural Language Processing” will return results containing that exact phrase.

Advanced Search: Click on the menu icon (three horizontal lines) in the upper-left corner and select “Advanced search” to access advanced search options. Here, you can specify authors, publications, and date ranges.

Filters: Use the filters on the left-hand side to narrow down results by publication year, author, or journal. You can select “Since” to specify a particular year.

Step 4: Explore Search Results

Browse through the search results to identify relevant articles, papers, and books. Each result includes the title, authors, publication source, and a brief excerpt from the content.

Now, let’s create a table to organize and track the information from your search results:

Step 5: Access Full Text

Click on the title of a search result to access the full text of the article or paper. Some may require a subscription or purchase, while others are freely accessible.

Step 6: Review and Cite

Read the selected articles thoroughly, take notes, and cite them in your research. Make sure to note the key findings and contributions to your topic.

By following these steps and organizing your findings in a table like the one above, you can efficiently conduct research on your chosen topic using Google Scholar. This approach helps you keep track of relevant publications and easily access the information you need for your research project.

Final Remark

Google Scholar is like a huge treasure chest filled with knowledge. It’s a must-have tool for researchers, scholars, and students all over the world. If you learn how to use it well, you can have a successful research journey that helps us all understand more about the world. Whether you’re looking for answers to specific questions or just curious about something, Google Scholar is your doorway to a world of academic learning. Check all above mentioned google scholar research topics. Try as per your requirement.

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• J Oncol Pract
• v.3(6); 2007 Nov

Developing Effective Communication Skills

A practicing oncologist likely uses just about every medium to communicate. They talk on the phone, send e-mail messages, converse one-on-one, participate in meetings, and give verbal and written orders. And they communicate with many audiences—patients and their families, referring physicians, and office staff.

But are you communicating effectively? How do you handle differing or challenging perspectives? Are you hesitant to disagree with others, especially those in authority? Do you find meetings are a waste of time? What impression does your communication style make on the members of your group?

Be an Active Listener

The starting place for effective communication is effective listening. “Active listening is listening with all of one's senses,” says physician communication expert Kenneth H. Cohn, MD, MBA, FACS. “It's listening with one's eyes as well as one's years. Only 8% of communication is related to content—the rest pertains to body language and tone of voice.” A practicing surgeon as well as a consultant, Cohn is the author of Better Communication for Better Care and Collaborate for Success!

Kenneth H. Cohn, MD, MBA, FACS

Cohn suggests creating a setting in which “listening can be accommodating.” For example, don't have a conversation when one person is standing and one person is sitting—make sure your eyes are at the same level. Eliminate physical barriers, such as a desk, between you and the other party. Acknowledge the speaker with your own body language: lean forward slightly and maintain eye contact. Avoid crossing your arms, which conveys a guarded stance and may suggest arrogance, dislike, or disagreement.

When someone is speaking, put a premium on “being present.” Take a deep breath (or drink some water to keep from speaking) and create a mental and emotional connection between you and the speaker. “This is not a time for multitasking, but to devote all the time to that one person,” Cohn advises. “If you are thinking about the next thing you have to do or, worse, the next thing you plan to say, you aren't actively listening.”

Suspending judgment is also part of active listening, according to Cohn. Encourage the speaker to fully express herself or himself—free of interruption, criticism, or direction. Show your interest by inviting the speaker to say more with expressions such as “Can you tell me more about it?” or “I'd like to hear about that.”

Finally, reflect back to the speaker your understanding of what has been said, and invite elaboration and clarification. Responding is an integral part of active listening and is especially important in situations involving conflict.

In active listening, through both words and nonverbal behavior, you convey these messages to the speaker:

• I understand your problem
• I know how you feel about it
• I am interested in what you are saying
• I am not judging you

Communication Is a Process

Effective communication requires paying attention to an entire process, not just the content of the message. When you are the messenger in this process, you should consider potential barriers at several stages that can keep your intended audience from receiving your message.

Be aware of how your own attitudes, emotions, knowledge, and credibility with the receiver might impede or alter whether and how your message is received. Be aware of your own body language when speaking. Consider the attitudes and knowledge of your intended audience as well. Diversity in age, sex, and ethnicity or race adds to the communication challenges, as do different training backgrounds.

Individuals from different cultures may assign very different meanings to facial expressions, use of space, and, especially, gestures. For example, in some Asian cultures women learn that it is disrespectful to look people in the eye and so they tend to have downcast eyes during a conversation. But in the United States, this body language could be misinterpreted as a lack of interest or a lack of attention.

Choose the right medium for the message you want to communicate. E-mail or phone call? Personal visit? Group discussion at a meeting? Notes in the margin or a typed review? Sometimes more than one medium is appropriate, such as when you give the patient written material to reinforce what you have said, or when you follow-up a telephone conversation with an e-mail beginning, “As we discussed.…”

For one-on-one communication, the setting and timing can be critical to communicating effectively. Is a chat in the corridor OK, or should this be a closed-door discussion? In your office or over lunch? Consider the mindset and milieu of the communication receiver. Defer giving complex information on someone's first day back from vacation or if you are aware of situations that may be anxiety-producing for that individual. Similarly, when calling someone on the phone, ask initially if this is a convenient time to talk. Offer to set a specific time to call back later.

Finally, organize content of the message you want to communicate. Make sure the information you are trying to convey is not too complex or lengthy for either the medium you are using or the audience. Use language appropriate for the audience. With patients, avoid medical jargon.

Be Attuned to Body Language—Your Own and Others

Many nonverbal cues such as laughing, gasping, shoulder shrugging, and scowling have meanings that are well understood in our culture. But the meaning of some of these other more subtle behaviors may not be as well known. 1

Hand movements. Our hands are our most expressive body parts, conveying even more than our faces. In a conversation, moving your hand behind your head usually reflects negative thoughts, feelings, and moods. It may be a sign of uncertainty, conflict, disagreement, frustration, anger, or dislike. Leaning back and clasping both hands behind the neck is often a sign of dominance.

Blank face. Though theoretically expressionless, a blank face sends a strong do not disturb message and is a subtle sign to others to keep a distance. Moreover, many faces have naturally down turned lips and creases of frown lines, making an otherwise blank face appear angry or disapproving.

Smiling. Although a smile may show happiness, it is subject to conscious control. In the United States and other societies, for example, we are taught to smile whether or not we actually feel happy, such as in giving a courteous greeting.

Tilting the head back. Lifting the chin and looking down the nose are used throughout the world as nonverbal signs of superiority, arrogance, and disdain.

Parting the lips. Suddenly parting one's lips signals mild surprise, uncertainty, or unvoiced disagreement.

Lip compression. Pressing the lips together into a thin line may signal the onset of anger, dislike, grief, sadness, or uncertainty.

Build a Team Culture

In oncology, as in most medical practices, much of the work is done by teams. Communication within a team calls for clarifying goals, structuring responsibilities, and giving and receiving credible feedback.

“Physicians in general are at a disadvantage because we haven't been trained in team communication,” says Cohn. He points out that when he was in business school, as much as 30% to 50% of a grade came from team projects. “But how much of my grade in medical school was from team projects? Zero.”

The lack of systematic education about how teams work is the biggest hurdle for physicians in building a team culture, according to Cohn. “We've learned team behaviors from our clinical mentors, who also had no formal team training. The styles we learn most in residency training are ‘command and control’ and the ‘pace setting approach,’ in which the leader doesn't specify what the expectations are, but just expects people to follow his or her example.”

Cohn says that both of those styles limit team cohesion. “Recognizing one's lack of training is the first step [in overcoming the hurdle], then understanding that one can learn these skills. Listening, showing sincere empathy, and being willing to experiment with new leadership styles, such as coaching and developing a shared vision for the future are key.”

Stated goals and team values. An effective team is one in which everyone works toward a common goal. This goal should be clearly articulated. In patient care, of course, the goal is the best patient outcomes. But a team approach is also highly effective in reaching other goals in a physician practice, such as decreasing patient waiting times, recruiting patients for a clinical trial, or developing a community education program. Every member of the team must be committed to the team's goal and objectives.

Effective teams have explicit and appropriate norms, such as when meetings will be held and keeping information confidential. Keep in mind that it takes time for teams to mature and develop a climate of trust and mutual respect. Groups do not progress from forming to performing without going through a storming phase in which team members negotiate assumptions and expectations for behavior. 2

Clear individual expectations. All the team members must be clear about what is expected of them individually and accept their responsibility for achieving the goal. They should also understand the roles of others. Some expectations may relate to their regular job duties; others may be one-time assignments specific to the team goal. Leadership of the team may rotate on the basis of expertise.

Members must have resources available to accomplish their tasks, including time, education and equipment needed to reach the goal. Openly discuss what is required to get the job done and find solutions together as a team.

Empowerment. Everyone on the team should be empowered to work toward the goal in his or her own job, in addition to contributing ideas for the team as a whole. Physicians' instinct and training have geared them to solve problems and give orders—so they often try to have all the answers. But in an effective team, each team member feels ownership in the outcome and has a sense of shared accountability. Cohn notes, “You get a tremendous amount of energy and buy-in when you ask ‘What do you think?’”

Team members must trust each other with important tasks. This requires accepting others for who they are, being creative, and taking prudent risks. Invite team members to indicate areas in which they would like to take initiative. Empower them by giving them the freedom to exercise their own discretion.

Feedback. Providing feedback on performance is a basic tenet of motivation. For some goals, daily or weekly results are wanted, while for others, such as a report of the number of medical records converted to a new system or the average patient waiting times, a monthly report might be appropriate. Decide together as a team what outcomes should be reported and how often.

Positive reinforcement. Team members should encourage one another. Take the lead and set an example by encouraging others when they are down and praising them when they do well. Thank individuals for their contributions, both one on one and with the team as a whole. Celebrate milestones as a way to sustain team communication and cohesion.

Effective E-mail

E-mail has numerous features that make it a wonderful tool for communicating with a team: it is immediate; it is automatically time-stamped; and filing and organizing are easy. (E-mail with patients is a more complex topic and is not addressed herein.)

The e-mail subject line is an especially useful feature that is typically underused. Make it your best friend. Use it like a newspaper headline, to draw the reader in and convey your main point or alert the reader to a deadline. In the examples given below, the person receiving an e-mail headed “HCC” is likely to scroll past it—planning to read it on the weekend. The more helpful subject line alerts the reader to be prepared to discuss the topic at an upcoming meeting:

•      Vague Subject Line: HCC
•      More Helpful Subject Line: HCC Plan to discuss the SHARP trial this Friday—Your comments due December 5 on attached new policies

As with all written communication, the most important aspect to consider is the audience. Consider the knowledge and biases of the person/people you are e-mailing. Where will the reader be when he or she receives your message? How important is your message to the reader?

The purpose of writing is to engage the reader. You want the reader to do something, to know something, or to feel something. Write it in a way that helps the reader. Put the most important information—the purpose of the email—in the first paragraph.

Except among friends who know you well, stay away from sarcasm in e-mail messages. The receiver does not have the benefit of your tone of voice and body language to help interpret your communication. When delivering comments that are even slightly critical, it's better to communicate in person or in a phone call than to do so in an e-mail. Something you wrote with good intentions and an open mind or even with humor can be interpreted as nitpicky, negative, and destructive, and can be forwarded to others.

Because we use e-mail for its speed, it's easy to get in the habit of dashing off a message and hitting the “send” button. We count on the automatic spell-check (and you should have it turned on as your default option) to catch your errors. But spelling typos are the least of the problems in communicating effectively.

Take the time to read through your message. Is it clear? Is it organized? Is it concise? See if there is anything that could be misinterpreted or raises unanswered questions. The very speed with which we dash off e-mail messages makes e-mail the place in which we are most likely to communicate poorly.

Finally, don't forget to supply appropriate contact information, including phone numbers or alternative e-mail addresses, for responses or questions.

Conflict is inevitable in times of rapid change. Effective communication helps one avoid conflict and minimize its adverse consequences when it does occur. The next issue of Strategies for Career Success will cover conflict management.

What Not to Do When Listening:

• Allow distractions
• Use clichéd phrases such as “I know exactly how you feel,” “It's not that bad,” or “You'll feel better tomorrow”
• Get pulled into responding emotionally
• Change the subject or move in a new direction
• Rehearse in your head what you plan to say next
• Give advice

Make Meetings Work for Your Team

A good meeting is one in which team goals are introduced or reinforced and solutions are generated. The first rule—meet in person only if it's the best format to accomplish what you want. You don't need a meeting just to report information. Here are tips for facilitating an effective meeting:

Don't meet just because it's scheduled. If there are no issues to discuss, don't hold the meeting just because it's Tuesday and that's when you always meet.

Use an agenda. Circulate a timed agenda beforehand and append useful background information. Participants should know what to expect. If it's a short meeting or quickly called, put the agenda on a flipchart or board before people arrive.

Structure input. Promote the team culture by making different individuals responsible for specific agenda items. Follow-up on previous task assignments as the first agenda item to hold group members accountable for the team's success.

Limit the meeting time. Use the timed agenda to stay on track. If the discussion goes off on a tangent, bring the group back to the objective of the topic at hand. If it becomes clear that a topic needs more time, delineate the issues and the involved parties and schedule a separate meeting.

Facilitate discussion. Be sure everyone's ideas are heard and that no one dominates the discussion. If two people seem to talk only to each other and not to the group as a whole, invite others to comment. If only two individuals need to pursue a topic, suggest that they continue to work on that topic outside the meeting.

Set ground rules up front. Keep meetings constructive, not a gripe session. Do not issue reprimands, and make it clear that the meeting is to be positive and intended for updates, analysis, problem solving, and decision making. Create an environment in which disagreement and offering alternative perspectives are acceptable. When individuals do offer opposing opinions, facilitate open discussion that focuses on issues and not personalities.

Circulate a meeting summary before the next meeting. Formal minutes are appropriate for some meetings. But in the very least, a brief summary of actions should be prepared. Include decisions reached and assignments made, with deadlines for follow-up at the next meeting.

Kenneth H. Cohn: Better Communication for Better Care: Mastering Physician-Administrator Collaboration. Chicago, IL, Health Administration Press, 2005, www.ache.org/pubs/redesign/productcatalog.cfm?pc=WWW1-2038

Kenneth H. Cohn: Collaborate for Success! Breakthrough Strategies for Engaging Physicians, Nurses, and Hospital Executives. Chicago, IL, Health Administration Press, 2006, www.ache.org/hap.cfm

Suzette Haden Elgin: Genderspeak: Men, Women, and the Gentle Art of Verbal Self-Defense. Hoboken, NJ, Wiley, 1993

Jon R. Katzenbach, Douglas K. Smith: The Wisdom of Teams: Creating the High Performance Organization. New York, NY, Harper Business, 1994

Sharon Lippincott: Meetings: Do's, Don'ts, and Donuts. Pittsburgh, PA, Lighthouse Point Press, 1994

Kenneth W. Thomas: Intrinsic Motivation at Work: Building Energy and Commitment. San Francisco, CA, Berrett-Koehler Publishers, 2000

More Strategies for Career Success!

Deciding About Practice Options—J Oncol Pract 2:187-190, 2006

The Interview: Make it Work for You—J Oncol Pract 2:252-254, 2006

Employment Contracts: What to Look for—J Oncol Pract 2:308-311, 2006

Principles and Tactics of Negotiation—J Oncol Pract 3:102-105, 2007

Professional Advisors: They're Worth It—J Oncol Pract 3:162-166, 2007

Building and Maintaining a Referral Base—J Oncol Pract 3:227-230, 2007

Malpractice Insurance: What You Need to Know—J Oncol Pract 3:274-277, 2007

Joining a Practice As a Shareholder—J Oncol Pract 3:41-44, 2007.

Gender differences in google scholar representation and impact: an empirical analysis of political communication, journalism, health communication, and media psychology

• Open access
• Published: 16 February 2024
• Volume 129 , pages 1719–1737, ( 2024 )

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• Manuel Goyanes 1 ,
• Tamás Tóth 2 &
• Gergő Háló   ORCID: orcid.org/0000-0002-7656-4043 2  

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Improving gender equality in top-tier scholars and addressing gender bias in research impact are among the significant challenges in academia. However, extant research has observed that lingering gender differences still undermine female scholars. This study examines the recognition of female scholars through Google Scholar data in four different subfields of communication, focusing on two pressing issues: (1) gender representation among the most cited scholars and (2) gender differences in citations. Our findings demonstrate significant differences in gender proportions among the most cited scholars across all subfields, but especially in Political Communication and Journalism. The regression analysis revealed significant differences in citation scores in Political Communication, Journalism, and the pooled sample. However, results revealed that gender differences in research impact were not statistically significant in Health Communication and Media Psychology. Our study advocates for shifts in the citing behavior of communication scholars, emphasizing the importance of actively recognizing and citing studies conducted by female researchers to drive advancements in communication research.

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Avoid common mistakes on your manuscript.

Research evaluation frameworks play a crucial role in “objectively” measuring scientific meritocracy (Kamdem et al., 2019 ; Khan et al., 2022 ), especially since the number of open academic positions is not keeping pace with the growing number of PhD graduates (Cyranoski et al., 2011 ). Although there are great concerns about evaluation processes’ fairness and procedures, scholars have been positively or negatively evaluated by these institutions in many countries (Lawrence et al., 2014 ; Park & Gordon, 1996 ). However, decades of field research have shown that beyond personality traits, such as talent or curiosity, individual and structural factors may also significantly influence different dimensions of scientific performance, such as productivity and impact (Cameron et al., 2016 ; Dion et al., 2018 ). In this study, we focus on one of the most important structural factors that might affect scholars’ recognition, namely gender roles .

Extant research has systematically examined gender roles and their possible effects on sex bias in scientific productivity and impact (Knobloch-Westerwick & Glynn, 2013 ). One of the most important theoretical pillars of studying academic gender bias is the Matilda effect , which posits that female scholars suffer lingering structural inequalities that constrain their career prospects (Rossiter, 1993 ). Scholars have explored the Matilda effect from different research angles, such as females’ and males’ research performance, impact, gender ratios of authors in academic publications, decisions on tenure track positions, or the likelihood of being funded (Dion et al., 2018 ; Freelon et al., 2023 ; Huang et al., 2020 ; Knobloch-Westerwick & Glynn, 2013 ). This article complements this research tradition and focuses on citations, one of the most important factors in heuristically estimating scientific impact (Judge et al., 2007 ). Citation counts are ultimate elements that might affect hiring, promotion, and grant decisions (Cameron, 2005 ; Feeley & Yang, 2022 ; Holden et al., 2005 ; Toutkoushian, 1994 ).

Although several studies have examined the Matilda effect in the field of communication (Feeley & Yang, 2022 ; Freelon et al., 2023 ; Knobloch-Westerwick & Glynn, 2013 ; Knobloch-Westerwick et al., 2013 ), little is known about how gender differences unfold in Google Scholar, one of the most important platforms to openly disclose scholars’ research impact across fields and research topics (Marsicano et al., 2022 ). Accordingly, focusing on four different subfields of communication research (Political Communication, Journalism, Health Communication, and Media Psychology) the aim of this paper is twofold: (1) to examine gender proportions among the most cited scholars within and across these subfields and (2) to explore gender differences in their citation counts. Footnote 1

Analyzing these research fields is important because of the particularly marked struggle in social sciences to achieve a dominant position in knowledge production (de Sousa Santos, 2018 ; Wallerstein, 1999 ) an aspect which, according to extant research, harms the recognition of females’ scientific contributions in communication research (Knobloch-Westerwick & Glynn, 2013 ; Knobloch-Westerwick et al., 2013 ). We analyze the fields of Political Communication, Journalism, Health Communication, and Media Psychology, because the former two disciplines are closer to “masculine” fields, while the others are closer to “feminine” topics in the sense of the role congruity theory (Knobloch-Westerwick & Glynn, 2013 ; Knobloch-Westerwick et al., 2013 ). Therefore, we aim to find out whether females are under-recognized in “masculine” and “feminine” subfields considering their presence (e.g., the number of women scientists) and impact (citation counts) among the top-cited researchers in Google Scholar.

Google scholar: A novel star

Generally, scholars use various academic search engines for research purposes (Gusenbauer, 2019 ). Google Scholar, launched in 2004, is interesting in particular because it is estimated to be the most comprehensive scientific search engine, with more than 389 million records (Gusenbauer, 2019 ). In addition, Google Scholar provides metadata for and/or the full text of scientific literature, and tracks citations, including self-citations, h-, and i-10 indexes (Singh et al., 2022 ).

Due to its growing popularity, researchers compared Google Scholar’s citation counts to other databases, such as Web of Science and Scopus (Amara & Landry, 2012 ; Etxebarria & Gomez-Uranga, 2010 ; Franceschet, 2010 ; Harzing & Alakangas, 2016 ; Mikki, 2010 ; Mingers & Lipitakis, 2010 ; Wildgaard, 2015 ). Franceschet ( 2010 ) outlined that Google Scholar detects a significantly higher number of citations and h-indexes than Web of Science, probably due to Google Scholar’s more inclusive crawling methods. Mingers and Lipitakis ( 2010 ) compared citation numbers in Google Scholar to the same metrics in Web of Science in the research fields of Business and Management. They suggested that Web of Science should not be taken into account in citation-based evaluations in social sciences because it covers less than half of the journals, papers, and citations detected by Google Scholar (Mingers & Lipitakis, 2010 ).

In line with the above results, Wildgaard ( 2015 ) found that Web of Science and Google Scholar provided remarkably different numbers of citations and publications and detected diverging numbers of co-authors in Astronomy, Environmental Science, Philosophy, and Public Health. Consequently, Wildgaard ( 2015 ) emphasized that extreme caution is needed when considering only one of the aforementioned databases to evaluate the scientific impact because “the same indicators calculated for the same scholar, but in two different databases, might provide a different picture of the scholar’s impact” (Wildgaard, 2015 , pp. 897–898). In contrast, another research (Mikki, 2010 ) revealed that Google Scholar detected 85% of Earth Science documents that emerged in the Web of Science and showed that the number of citations and h-indexes were very similar in the two databases. Harzing’s and Alakangas’ ( 2016 ) longitudinal and cross-disciplinary analysis also found that Web of Science, Scopus, and Google Scholar provided stable and consistent growth in publication and citation metrics, suggesting that all of these databases have the stability of coverage that is necessary for more in-depth cross-disciplinary comparisons.

Regarding recent studies, Thelwall and Kousha ( 2017 ) revealed that Google Scholar collects more citations than ResearchGate, Web of Science, and Scopus. They also argued that Google Scholar and ResearchGate might not utilize different data sources for indexing citations because their citation counts strongly correlate with each other’s metrics (Thelwall & Kousha, 2017 ). Singh and colleagues ( 2022 ) found that Google Scholar outperformed ResearchGate in citation metrics when they analyzed highly cited authors. They outlined the possible reasons why Google Scholar is “more successful” in crawling citations. Two of these reasons are crucial. First, Google Scholar has a more universal and less stringent indexing policy that collects a wide range of electronic documents: it crawls both peer-reviewed articles and the grey literature. Second, while Google Scholar automatically assigns a publication to a researcher, ResearchGate “sometimes fails to automatically attribute publications to the correct author” (Singh et al., 2022 , p. 1535). Finally, researchers also found that scientists have more impressive bibliometric results in Google Scholar than in Scopus (Marsicano et al., 2022 ). The explanation relied again on the extensive search methods that Google Scholar implements (Marsicano et al., 2022 ).

Even though Google Scholar’s popularity is perceived and acknowledged, it also has some pitfalls (Marsicano et al., 2022 ). First and foremost, Google Scholar was criticized for containing specific types of “errors,” such as including non-scholarly documents (Jacsó, 2012a ). In addition, researchers observed that Google Scholar might duplicate documents, thus potentially inflating citation scores (Doğan et al., 2016 ; Jacsó, 2006b ). Consequently, Jacsó ( 2006a ) suggests that Google Scholar is “good for locating relevant items, leading users some of the time to an open access version of a document, but it is not an appropriate tool for bibliometric studies” (p. 307) because it “ plays fast and loose, (make that too fast and too loose), with its hit counts and citation counts to allow fair comparisons without tiresome verification” (p. 307). However, scholars found that double citations originating from redundant versions of the same paper occur in less than 2% of the observed cases on this platform (Moed et al., 2016 ). Finally, bibliometric information may overlap in Google Scholar if the imported data is incorrectly added to research profiles where scholars have identical names or surnames.

Even though researchers highlight that Google Scholar utilizes questionable and opaque indexing methods (Jacsó, 2005 , 2012b ), the relevance and magnitude of this academic search engine are difficult to disregard. Therefore, we argue that analyzing the Matilda effect in representation and citations within Google Scholar is an important step toward a better understanding of potential gender bias in the subfields of communication studies. For that, as to the best of our knowledge no previous analyses addressed the Matilda effect within Google Scholar with regards to communication science, by doing so we offer fresh insights into the representation and citation patterns of the field considering one of the most important platform for research evaluation. In the subsequent sections, we introduce the significance of analyzing top-cited scholars, as well as the Matilda effect among these researchers and in citations before we outline our research questions.

The significance of analyzing top-cited scholars

The examination of the most cited scholars within a specific field plays a pivotal role in understanding the development of sciences, shedding light on the overall state of knowledge production. Examining the top-cited scholars allows for the identification of individuals who wield significant influence in steering the direction of a field. Their work is often at the forefront of new (methodological and/or theoretical) developments within their respective disciplines, shaping the intellectual evolution of scientific fields (Kwiek, 2018 ). By focusing on the most cited scholars, this study, while recognizing the broader complexities and potential limitations associated with this approach, offers insightful findings on the gender representation and gender differences in citations in one of the most important collectives in shaping the course of science (Bolkan et al., 2012 ; Cucari et al., 2023 ).

Matilda effect in authorship and citations

In 1968, Merton introduced the Matthew effect, which focuses on two intertwined phenomena: the over-recognition of top scholars and the under-recognition of lesser-known scientists. The Matthew effect outlines that acknowledged scientists gain enhanced visibility while their less recognized peers’ contributions fade away (Merton, 1968 ). This paper’s primary theoretical background is a phenomenon entitled the Matilda effect—a term coined in relation to the Matthew effect—which presumes that female scientists are less recognized than their male colleagues (Rossiter, 1993 ). For instance, studies have proved that, as they reviewed progressively higher academic positions, they found a constant decrease in the number of female scholars in these roles (European Commission, 2012 ; National Academy of Sciences, 2007 ; van den Besselaar & Sandström, 2017 ). Research also showed that female scholars win smaller grants than their male colleagues (RAND Corporation, 2005 ) and receive scholarships with considerably less frequency than male scientists (Bornmann et al., 2007 ; Lerchenmueller & Sorenson, 2018 ; Liao & Lian, 2022 ; van den Besselaar & Leydesdorff, 2009 ). It is important to note, however, that many studies found no gender bias in publishing, hiring, and being funded (Ceci & Williams, 2011; Ley & Hamilton, 2008 ; Liao & Lian, 2022 ).

A vital question emerges at this point: what factors might fuel the Matilda effect? The answer relies primarily on socially constructed, structural reasons. Considering the literature on gender bias in science, the relevant theoretical background is rooted in social role theory, whereby scholars argue that gender is socially constructed via gender roles (Eagly, 1987 ). These roles implement normative expectations from males and females and suggest the desirable behavior for men and women (Eagly, 1987 ). The social role theory suggests that communal characteristics mostly suit women while agentic ones are generally desirable for men (Eagly, 1987 ). Specifically, communal characteristics imply helpful, caring, and sympathetic attitudes towards other people’s well-being, while agentic characteristics are typical of competitive, ambitious, self-confident individuals with strong leadership skills (Knobloch-Westerwick et al., 2013 ). At this point, an important segment of the theory, the role congruity theory , kicks in.

The role congruity theory helps scholars analyze the congruity between gender roles and other roles, such as the scientific one (Eagly & Karau, 2002 ). Role congruity theory suggests that scientific roles are agentic, and therefore are closer to “male” characteristics, implying ambition, leadership, and self-confidence (Knobloch-Westerwick & Glynn, 2013 ). On the other hand, role congruity theory highlights that communal roles—such as taking care of children and ill people—are not compatible with the scientific role. Consequently, beliefs about the scientist and female roles are not compatible, which leads to competition between these role-based expectations. Role incongruity might harm female scientists by causing them to be judged negatively in academia. As a result, the social–psychological incongruity might attract negative evaluations or reduce the willingness to invite female scientists to research networks (Knobloch-Westerwick et al., 2013 ). These structural circumstances can reduce the duration of females’ careers and harm their productivity, because structural factors such as negative stereotypes towards women, exclusion from informal networks of communication, and the lack of professional mentors might be due to role incongruity (Cech & Blair-Loy, 2014 ; Huang et al., 2020 ).

Beyond the well-known structural reasons, other explanations might also be relevant in examining the Matilda effect. One of the most comprehensive papers on sex differences analyzed 1.5 million authors and found that women account for 27% of authorship in the research fields of science, technology, engineering, and mathematics (Huang et al., 2020 ). Researchers explained the above difference with different dropout rates for females at every stage of their careers (Huang et al., 2020 ). Dropout rates might be higher for women than men because females report exclusion from colleagues, aggressive behavior from students, and sexual harassment during their faculty work more often than males (Bronstein & Farnsworth, 1998 ). Another research (Leahey, 2006 ) suggested that specialization supports productivity, but that female sociologists tend not to focus on a single research field because they feel that narrowing down their research scope would harm their competitiveness when they try to move to other institutions or departments. Duch et al. ( 2012 ) argue that female scholars’ lower publication rates are possibly due to the fact that women gain less institutional support in research resource amounts than their male peers.

Extant research also found that women participate significantly less in international research collaboration than men (Uhly et al., 2017 ). Importantly, the above study also revealed that family status can create an invisible “glass fence” that harms females’ academic careers if women have partners who do not work in academia (Uhly et al., 2017 ). Jadidi et al. ( 2018 ) argue that female scholars are less prolific than men because they work with a smaller fraction of senior authors than males, narrowing women’s research networks. The study revealed that successful male and female scholars had the same collaborative behavior: both groups work with “highly-connected scientists” (Jadidi et al., 2018 , p. 18) who produce many peer-reviewed papers with high quality. Van den Besselaar and Sandström ( 2017 ) argue that the Matilda effect in production is explained by the facts that (1) male scholars are older in general and have more time to publish and (2) men have higher academic positions. The above study suggests that the higher academic position scholars have, the more prolific they are, and women are in a disadvantaged position in that competition.

As for the field of communication, a recent study has found that the number of female first authors grew significantly between 2009 and 2019, but their proportion among the top-cited authors did not grow at a similar pace (Author et al. 2022). More specifically, even though the share of female scholars (57%) was larger in 2019 than their male counterparts’ ratio in communication research, males outperformed (58%) their female peers’ shares in the first authorship among the top-cited researchers (Author et al., 2022). Even though another study revealed that gender imbalance has decreased in the last two decades among the most cited communication scholars’ proportion, almost three-quarters (74.3%) of them are still (white) men (Freelon et al., 2023 ). Although the above research explored how the Matilda effect prevails in gender ratios in authorship and among leading scholars in the prominent segments of communication studies, we still do not have information on possible gender proportions among the most cited authors in Google Scholar. Therefore, we formulate the following research question:

RQ1) Are there equal gender proportions in Google Scholar among the most cited scholars in (a) Political Communication, (b) Journalism, (c) Health Communication, (d) Media Psychology, and (e) the pooled sample?

Ample evidence suggests that a gendered citation gap persists in sciences and male scholars receive more citations than their female peers (Dion et al., 2018 ). Again, what might cause the Matilda effect in receiving citations? Dion and colleagues ( 2018 ) consider two important factors: productivity gaps and differences in self-citations. First, males tend to be more prolific than women because they occupy higher positions, work in larger research networks, win more funds, have smaller dropout rates during their careers, spending less time on caregiving, and possibly have less or no career breaks while they work in academia (Huang et al., 2020 ). Second, men are willing to cite their own papers more frequently than women, which is theoretically labelled as gender homophily in citations (Hutson, 2006 ; Maliniak et al., 2013 ; Potthoff & Zimmermann, 2017 ; Zigerell, 2015 ).

Nevertheless, regarding gender bias in citations, Dion and colleagues emphasize that it is “difficult to know if this occurs simply because men publish and cite themselves more than women or if scholars systematically fail to cite relevant work by women in their field (or both)” ( 2018 , p. 315). What is more important, however, is that the Matilda effect in citations is detrimental because it disregards many women’s works and findings that should be introduced in papers, monographs, book chapters, textbooks, and courses at academic institutions (Colgan, 2017 ; Hardt et al., 2017 ). If many female scholars’ findings are marginalized, a large part of the scientific work might fade away, and inequalities will be maintained in academia, where diverse knowledge production should be essential, if not paramount.

Several studies have analyzed the possible gender gaps within the citation patterns of published papers to investigate the prevalence of the Matilda effect, but their outcomes are contradictory. On the one hand, the Matilda effect emerges in the research fields of Ecology (Cameron et al., 2016 ), Economics (Ferber, 1988 ; Ferber & Brün, 2011 ), Library and Information Sciences (Håkanson, 2005 ), Mathematics (Aksnes et al., 2011 ), and Political Science (Maliniak et al., 2013 ). On the other hand, there was no Matilda effect in citations in Biochemistry (Long, 1992 ), Construction Studies (Powell et al., 2009 ), Criminal Justice (Stack, 2002 ), Economic History (Di Vaio et al., 2012 ), Geography (Slyder et al., 2011 ), International Relations (Østby et al., 2013 ), Public Administration (Corley & Sabharwal, 2010 ), and Sociology (Ward, 1992 ).

In communication research, important analyses considering citations were conducted on gender gaps. In line with the role congruity theory (Eagly & Karau, 2002 ), scholars found that male researchers are cited more than females in Communication Research and the Journal of Communication (Knobloch-Westerwick & Glynn, 2013 ). Another study found that male scholars cite their male peers more often than they cite female researchers, and vice versa, thus proving gender homophily in citations in two leading German communication studies journals (Potthoff & Zimmermann, 2017 ). This gender homophily in citations is partly due to differences in male and female communication scholars’ research interests (Potthoff & Zimmermann, 2017 ). Based on the results of the structural equation modeling in the aforementioned study, male authors tend to be cited more than female authors. This conclusion was drawn from the model which demonstrated that the gender composition of authors (higher values indicating higher impact of male authors) and “masculine” / “feminine” research subjects affect the proportion of female authors cited. The gender composition of authors had a negative effect on the choice of female-typed research subjects, and a positive effect on male-typed research subjects, which in turn affects the proportion of female authors cited (Potthoff & Zimmermann, 2017 ). Recent research also highlighted that even though female communication scholars’ publications are viewed more than the work of their male colleagues, women’s papers are cited less than male authors’ publications (Author, 2022b). In contrast, Feeley and Yang ( 2022 ) analyzed the number of (self-)citations in eight communication journals and found that the Matilda effect emerged “only” in Health Communication and Political Communication and that the effect was minor. However, they also argue that males were more likely to self-cite their own papers in six journals than females. Against this backdrop, we outline the following research question:

RQ2) How does gender affect citation counts in a) Political Communication, b) Journalism, c) Health Communication, d) Media Psychology, and e) the pooled sample?

Google Scholar is a growing platform that measures researchers’ publications and citation counts across years (Marsicano et al., 2022 ). Its use has grown in recent years, even in research evaluation processes (Hayashi, 2019 ). The platform allows users to summarize their research production by linking each research item to a given citation score provided by Google Scholar’s search algorithm. The platform also allows users to outline their individual research fields via research labels and ranks the most cited scholars according to their citation scores. Although research output and citation counts might be occasionally misreported by Google Scholar or researchers, it is a platform that can be used to assess impact and productivity in several evaluation processes.

Data for this study was directly computed from Google Scholar. To gather individual level data from the four subfields, the top 100 hundred most cited scholars were examined by selecting each discipline in Google Scholar (n = 400). We coded all data for every scholar across subfields on the same day (22/06/2022) to avoid discrepancies in citation counts and research output, as highly cited scholars may increase bibliometrics from one day to another. We rely on citation counts, productivity, and years of experience (measured as the total number of years since the first citation) as reported directly in Google Scholar. If coders detected inconsistencies at individual level data, records were manually corrected: false positives (i.e., fake or irrelevant profiles) were removed from the dataset, introducing the subsequent profiles within the subfield list. In such cases, scholars’ production was manually reviewed to detect mismatches between research interest and research output (for instance, scholars interested in Journalism and publishing in Aeronautics).

However, in most cases, the most cited scholars in the four subfields under scrutiny had accurate profiles, thus such corrections were minimal. For the pooled sample, subfields were merged and duplicates were removed (i.e., scholars cross-listed in two or more subfields, n = 25). Regarding intercoder agreement, the first author independently coded a random selection of 20% of observations the same day of the original data collection and disagreements were not found (100% agreement for gender, 100% for citation counts, 100% for research output, and 100% for year since first citation). The variables of interest are explained below.

Dependent and Independent Variables

Subfields. This variable taps on four subfields plus the pooled sample (collapsing the four subfields into one value): Political Communication, Journalism, Health Communication, and Media Psychology. We chose the categories included in this study based on the size, thematic patterns, influence, and diversity of the given subfield within communication studies. Furthermore, the chosen subfields are also represented in ICA divisions, indicating their relevance and magnitude within the wider field.

Gender. This variable deals with the gender of the author under review. We consider the typical divide in scientometric analysis (male vs. female) by manually checking the name reported in Google Scholar and the personal photograph. In case of uncertainty, coders made Google searches to clarify the gender of the scholar. This variable is considered the main independent variable in the regression models (males = 269; females = 106).

Citation count. Total number of citations that were reported at each individual profile of Google Scholar. This variable is the dependent variable in the regression models. Pooled sample (range = 63,198; mean = 8085; SD = 8249.32; skewness = 2.92, SD = 0.12; Kurtosis = 11.79, SD = 0.24), political communication (range = 42.269; mean = 10,269.20; SD = 8042.19; skewness = 2.47, SD = 0.24; Kurtosis = 7.06, SD = 0.47), journalism (range = 44,652; mean = 7709.18; SD = 6841.63; skewness = 2.92, SD = 0.24; Kurtosis = 11.54, SD = 0.47), media psychology (range = 57,826; mean = 4736.24; SD = 7811.64; skewness = 4.43, SD = 0.24; Kurtosis = 24.43, SD = 0.47), health communication (range = 60,985; mean = 9627.65; SD = 9114.18; skewness = 3, SD = 0.24; Kurtosis = 12.72, SD = 0.47).

As citation counts may be affected by both the levels of productivity and years of experience in academia (Li et al., 2017 ), our regression models controlled for both. Research suggests that levels of research productivity significantly and positively boost citation records (Li et al., 2017 ). Therefore, scholarly overproduction is likely to increase impact and visibility (Li et al., 2017 ). Likewise, scholars’ total citation records are significantly influenced by the years of experience since the first citation: the more years a researcher spends publishing, the better chance they have at accumulating high citation statistics.

Research output. This variable considers different types of research, such as papers, books, book chapters, conference proceedings, editorials, and all potential material subject to being cited by the scientific community and that has been manually or algorithmically uploaded by researchers or Google Scholar to the individual profiles. Pooled sample (range = 1116; mean = 151.01; SD = 116.03; skewness = 2.50, SD = 0.12; Kurtosis = 13.02, SD = 0.24), political communication (range = 512; mean = 156.17; SD = 93.03; skewness = 1.31, SD = 0.24; Kurtosis = 2.41, SD = 0.47), journalism (range = 625; mean = 163.95; SD = 108.82; skewness = 1.74, SD = 0.24; Kurtosis = 4.05, SD = 0.47), media psychology (range = 519; mean = 101.52; SD = 92.70; skewness = 2.04, SD = 0.24; Kurtosis = 4.56, SD = 0.47), health communication (range = 1092; mean = 182.42; SD = 146.65; skewness = 3.11, SD = 0.24; Kurtosis = 16.16, SD = 0.47).

Years since first citation. We compute the years since first citation by counting the number of years in a scholar’s Google Scholar profile (min = 5; max = 40; mean = 20.51; SD = 7.47).

Analysis strategy

In order to answer the research questions, we relied on two different statistical tests. First, to answer RQ1, we ran a series of χ 2 Goodness of Fit test, one for each subfield of study and one for the pooled sample, by collapsing all subfields. The minimum expected frequency for running this statistic was met. Second, to answer RQ2, we ran a series of bootstrap OLS-regression models. As assessed by a visual inspection of distributions, citation counts across subfields were not distributed normally. Accordingly, in order to provide reliable findings, the study ran a series of bootstrap OLS-regression models accounting for robust standard errors based on bootstrapping to 1,000 resamples with biased corrected confidence to assess statistical significance.

The first research question inquiries about the gender representation among the most cited Google Scholar researchers across different subfields of communication (see Table  1 ). The χ 2 Goodness of Fit test showed that there were statistically significant differences between the number of male and female scholars across every subfield and in the pooled sample. In other words, assuming equal proportions, there is a prominent male majority in the category of the most cited researchers. At the subfield level, the starkest underrepresentation is in Political Communication, with female scholars accounting for only 15% of the sample, followed by Journalism (21%), Media Psychology (33%), and Health Communication (41%). In the pooled sample, the situation is also quite unbalanced as females make up 28.26% of the most cited category.

A series of OLS-regressions were run to answer RQ2 for each subfield of study and the pooled sample. In Political Communication (see Table  2 ), after controlling for productivity (β = 0.51; p < 0.001) and years since first citation, female scholars are significantly less cited than their male peers (β = -0.09; p < 0.05).

Similarly, in Journalism (see Table  3 ) results of the regression analysis revealed that after controlling for productivity (β = 0.34; p < 0.05) and years since first citation, female scholars are significantly less cited than their male peers (β = -0.17; p < 0.05).

However, in Health Communication (see Table  4 ), the most balanced subfield in terms of gender representation among the most cited scholars (see RQ1 above), after controlling for productivity (β = 0.50; p < 0.01) and years since first citation (β = 0.18; p < 0.05), we found no statistically significant differences between male and female scholars’ citation scores.

In Media Psychology (see Table  5 ), the second most balanced subfield in terms of gender representation among the most cited scholars, after controlling for productivity (β = 0.54; p < 0.01) and years since first citation, we found no statistically significant differences between male and female scholars’ citation scores.

Finally, collapsing all subfields in the pooled sample (see Table  6 ), the regression analysis revealed that after controlling for productivity (β = 0.48; p < 0.001) and years since first citation (β = 0.19; p < 0.01), female scholars are significantly less cited than their male peers (β = -0.10; p < 0.05).

Discussion and conclusion

Extant research has investigated the Matilda effect in sciences, indicating significant gender biases in productivity, performance, and career paths (Dion et al., 2018 ; Huang et al., 2020 ). In the field of communication, studies explored gender-based citation disparities (Feeley & Yang, 2022 ; Freelon et al., 2023 ; Knobloch-Westerwick & Glynn, 2013 ; Knobloch-Westerwick et al., 2013 ). Although the overall inequalities are apparent, subfield-level analyses are still scarce, prompting a need for a deeper, high-resolution exploration. Therefore, we examined the gender proportions among the most cited scholars in Political Communication, Journalism, Health Communication, and Media Psychology, as well as the gender-based citation counts between them. Given the absence of prior analyses on the Matilda effect within Google Scholar (i.e., recent similar analysis by Freelon et al. ( 2023 ) apply WoS and Scopus data), we provide novel insights into the representation and citation patterns of top-cited researchers.

With regards to our first research questions, we found that, compared to their male peers, highly cited female authors are underrepresented in all subfields and in the pooled sample, regardless of whether the field is one traditionally considered masculine or feminine. These striking results are aligned with previous findings indicating a lack of balanced female representation among the top performing communication scholars (Freelon et al., 2023 ; Knobloch-Westerwick & Glynn, 2013 ). Importantly, disparities are substantial in the pooled sample, Political Communication, Journalism, and Media Psychology. While the overall picture in Health Communication is more gender balanced, it is still significantly skewed in favor of men.

The struggle to dominate academic knowledge production and impact in social sciences, including communication studies, is obvious. Although many researchers have focused on regional and economic aspects, suggesting that rich Western institutions dominate the poor, non-Western academia in publications and citations, gender is another structure that must be considered in academic inequalities (de Sousa Santos, 2018 ; Rossiter, 1993 ; Wallerstein, 1999 ). Gender bias in social sciences is interesting in particular because it also emerges within core institutions and not only in academia embedded in the periphery (Author, 2020). But how should this specific type of inequality be understood in this case? The role congruity theory supports the interpretation of why there was a significantly lower female presence among the top-cited communication researchers on Google Scholar (Eagly & Karau, 2002 ; Garcia-Retamero & López-Zafra, 2006 ; Knobloch-Westerwick & Glynn, 2013 ). Agentic features characterize the role of scientists, who are considered to be ambitious and career-oriented (Knobloch-Westerwick et al., 2013 ). These characteristics are aligned with male social roles rather than female roles, which are assumed to be community-oriented instead (Eagly, 1987 ).

To acquire citations, scholars must publish papers in highly prestigious journals, participate in large and prolific research networks, win grants, hold high academic positions, win scholarly awards and promotions, spend much time with research, attend international conferences, and share their publications via (academic) social sites (Demeter, 2020 ). The above factors are closer to the career-oriented, agentic roles rather than the “caring” communal ones. On top of that, these efforts require time. Time is crucial because earlier studies have observed that there is a higher proportion of female than male scholars at the lower rungs of academia level, indicating that women typically teach more than men, and thus have less time to participate in research and publish outstanding papers in prestigious journals (Author, 2020).

Additionally, the Matilda effect was outlined in 1993, and the empirical analysis of this research tradition harks back only a few decades. We take this into account because many scholars among the top-cited communication researchers published before the 1990s, when less attention was paid to citing females and males equally. Even though the Matilda effect theory is three decades old, it still needs time to gain prominence in scholarly analysis. Thus, studies with results similar to ours can highlight the importance of acknowledging – via citation records – women’s academic publications more frequently (Freelon et al., 2023 ).

Taking a closer look at our results on female underrepresentation among the top-cited scholars, we can interpret them from another angle. Our findings indicated that Political Communication and Journalism studies, which are typically portrayed as masculine research fields (Knobloch-Westerwick & Glynn, 2013 ), show the most serious female underrepresentation (15% and 21%) among the most cited scholars. In turn, Health Communication—that is, the field most connected to the notion of “care”—was the most balanced (41%). Prior studies (Holman et al., 2018 ; Larivière et al., 2013 ) have indicated a stronger male dominance in fields connected to policy making and social power, while politically less involved fields generally associated with “care,” tend to be more balanced. This explanation can be a relevant one if we try to understand the gender bias, which seems to be stratified among communication scholars on Google Scholar. In other words, even though each subfield analyzed is significantly male-dominated in terms of presence, the difference is smaller in Health Communication, possibly due to its proximity to the female social role that implies care (Knobloch-Westerwick & Glynn, 2013 ).

Notwithstanding, although most scientific fields are becoming more gender balanced over time (Elsevier, 2017 ), citation biases—as citations are accumulated over a relatively long time—still prevail. Consequently, in our second research question, we measured gender-based citations, controlling for academic experience (i.e., the years since their first citation) and productivity. After controlling for these measures, our study revealed female scholars to be significantly under-cited in the pooled sample as well as in the subfields of Political Communication and Journalism. Notwithstanding, in the case of Health Communication and Media Psychology, we found no significant differences in gender-based citations. That is, while in Health Communication and Media Psychology, the general under-recognition of female scholars can be attributed to the aforementioned slow process of adaptation of citation measures to progress in gender equality, the same cannot be stated for Political Communication and Journalism, emphasizing currently existing socio-cultural citation biases towards female scholars.

Our analysis also indicated that fields with similar proportions of females and males among the most cited scholars are also those in which gender differences in citation counts seem to disappear. Specifically, the regression analysis revealed significant differences in citation counts in Political Communication, Journalism, and the pooled sample. On the other hand, the more diverse fields of Health Communication and Media Psychology showed no significant biases concerning research impact based on gender after controlling for productivity and academic experience.

The outcomes on the gender differences in receiving citations outline the following conclusions. Even though many female scholars acquired positions among the top-cited communication researchers, the scientific community acknowledges their work equally if their research field is considered to be aligned with their “expected,” communal social characteristics. Media Psychology and Health Communication are closer to the communal roles than the other two subfields (Knobloch-Westerwick & Glynn, 2013 ). In other words, the underlying communal characteristics in Health Communication and Media Psychology “allow” female researchers to acquire unbiased level of recognition if they are first able to make their way into the elite league of the most cited scholars. Put differently, agentic characteristics are sufficient to be among the most recognized scholars but, for women, their subfield should contain communal social characteristics for them to acquire the same level of recognition as males in Health Communication and Media Psychology. In turn, “masculine” fields such as Political Communication and Media Psychology seem to resist females’ equal recognition because (1) the effort to get into the elite league of the most cited scholars needs agentic characteristics and (2) these subfields are “masculine” as they deal with power and influence on larger communities. As a result, the presence of the two, intertwined structural factors attached to Political Communication and Journalism are too strong to let female scholars receive the same recognition as males. Nevertheless, we contend that these subfields ought to adopt a more inclusive stance towards women, acknowledging and valuing their scientific contributions to prevent overlooking their impact. Fostering a mindful approach to citations is essential for advancing towards a more diverse and inclusive body of scientific knowledge.

Limitations and future research

As mentioned above, Google Scholar indexes grey literature that may inflate citation counts. Consequently, our results should be interpreted with caution, especially if compared with certain other databases such as Web of Sciences or Scopus. In addition, due to the unsupervised crawling methods of Google Scholar, fake profiles, fake papers or non-curated material can introduce important bias in measuring citations counts. Our analysis, fully aware of these potential biases of Google Scholar, tried to reduce the measurement error by consciously implementing a content analysis, and collecting data for all subfields and academics on the same day to prevent variations in their citations or production records. As a consequence of these limitations, we measured four diverse subfields within communication, yet future studies may also consider extending this analysis to other subfields of communication or other fields of sciences.

We also need to note that examining the top-cited scholars has limitations. Firstly, it concentrates on a narrow group of scholars, offering a limited perspective on general patterns of the fields under examination. Secondly, biases related to factors like gender and institutional affiliations may distort the analysis within this subset (Kwiek, 2018 ). To address these challenges, future research should broaden its focus to a more representative sample, ensuring a broader understanding of gender representation and research impact.

It is also important to note that there are certain limitations to the gender-based categorization of communication scientific subfields. As Knobloch-Westerwick and Glynn ( 2013 , pp. 12–13) pointed out: “Regarding gender-typed topics, 48 pieces (4.7%) fell into the “female-typed” category, 236 (23.1%) fell into the “male-typed” category, and 17 pieces (1.7%) were categorized to fall into both categories based on featuring strings associated with stereotypes for both genders. The vast majority of 711 (70.5%) emerged as “gender-neutral” based on the categorizations of gender-typed research topics”. Therefore, it is highly important to exercise caution when categorizing communication research topics based on gender stereotypes, as well as to avoid distinct dichotomous categories.

We utilize capital letters in the terms “Political Communication, Journalism, Health Communication, and Media Psychology” because we refer to the research fields and not the related phenomena.

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Goyanes, M., Tóth, T. & Háló, G. Gender differences in google scholar representation and impact: an empirical analysis of political communication, journalism, health communication, and media psychology. Scientometrics 129 , 1719–1737 (2024). https://doi.org/10.1007/s11192-024-04945-0

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Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research. Our analysis of a selection of questionable GPT-fabricated scientific papers found in Google Scholar shows that many are about applied, often controversial topics susceptible to disinformation: the environment, health, and computing. The resulting enhanced potential for malicious manipulation of society’s evidence base, particularly in politically divisive domains, is a growing concern.

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Research Questions

• Where are questionable publications produced with generative pre-trained transformers (GPTs) that can be found via Google Scholar published or deposited?
• What are the main characteristics of these publications in relation to predominant subject categories?
• How are these publications spread in the research infrastructure for scholarly communication?
• How is the role of the scholarly communication infrastructure challenged in maintaining public trust in science and evidence through inappropriate use of generative AI?

research note Summary

• A sample of scientific papers with signs of GPT-use found on Google Scholar was retrieved, downloaded, and analyzed using a combination of qualitative coding and descriptive statistics. All papers contained at least one of two common phrases returned by conversational agents that use large language models (LLM) like OpenAI’s ChatGPT. Google Search was then used to determine the extent to which copies of questionable, GPT-fabricated papers were available in various repositories, archives, citation databases, and social media platforms.
• Roughly two-thirds of the retrieved papers were found to have been produced, at least in part, through undisclosed, potentially deceptive use of GPT. The majority (57%) of these questionable papers dealt with policy-relevant subjects (i.e., environment, health, computing), susceptible to influence operations. Most were available in several copies on different domains (e.g., social media, archives, and repositories).
• Two main risks arise from the increasingly common use of GPT to (mass-)produce fake, scientific publications. First, the abundance of fabricated “studies” seeping into all areas of the research infrastructure threatens to overwhelm the scholarly communication system and jeopardize the integrity of the scientific record. A second risk lies in the increased possibility that convincingly scientific-looking content was in fact deceitfully created with AI tools and is also optimized to be retrieved by publicly available academic search engines, particularly Google Scholar. However small, this possibility and awareness of it risks undermining the basis for trust in scientific knowledge and poses serious societal risks.

Implications

The use of ChatGPT to generate text for academic papers has raised concerns about research integrity. Discussion of this phenomenon is ongoing in editorials, commentaries, opinion pieces, and on social media (Bom, 2023; Stokel-Walker, 2024; Thorp, 2023). There are now several lists of papers suspected of GPT misuse, and new papers are constantly being added. 1 See for example Academ-AI, https://www.academ-ai.info/ , and Retraction Watch, https://retractionwatch.com/papers-and-peer-reviews-with-evidence-of-chatgpt-writing/ . While many legitimate uses of GPT for research and academic writing exist (Huang & Tan, 2023; Kitamura, 2023; Lund et al., 2023), its undeclared use—beyond proofreading—has potentially far-reaching implications for both science and society, but especially for their relationship. It, therefore, seems important to extend the discussion to one of the most accessible and well-known intermediaries between science, but also certain types of misinformation, and the public, namely Google Scholar, also in response to the legitimate concerns that the discussion of generative AI and misinformation needs to be more nuanced and empirically substantiated  (Simon et al., 2023).

Google Scholar, https://scholar.google.com , is an easy-to-use academic search engine. It is available for free, and its index is extensive (Gusenbauer & Haddaway, 2020). It is also often touted as a credible source for academic literature and even recommended in library guides, by media and information literacy initiatives, and fact checkers (Tripodi et al., 2023). However, Google Scholar lacks the transparency and adherence to standards that usually characterize citation databases. Instead, Google Scholar uses automated crawlers, like Google’s web search engine (Martín-Martín et al., 2021), and the inclusion criteria are based on primarily technical standards, allowing any individual author—with or without scientific affiliation—to upload papers to be indexed (Google Scholar Help, n.d.). It has been shown that Google Scholar is susceptible to manipulation through citation exploits (Antkare, 2020) and by providing access to fake scientific papers (Dadkhah et al., 2017). A large part of Google Scholar’s index consists of publications from established scientific journals or other forms of quality-controlled, scholarly literature. However, the index also contains a large amount of gray literature, including student papers, working papers, reports, preprint servers, and academic networking sites, as well as material from so-called “questionable” academic journals, including paper mills. The search interface does not offer the possibility to filter the results meaningfully by material type, publication status, or form of quality control, such as limiting the search to peer-reviewed material.

To understand the occurrence of ChatGPT (co-)authored work in Google Scholar’s index, we scraped it for publications, including one of two common ChatGPT responses (see Appendix A) that we encountered on social media and in media reports (DeGeurin, 2024). The results of our descriptive statistical analyses showed that around 62% did not declare the use of GPTs. Most of these GPT-fabricated papers were found in non-indexed journals and working papers, but some cases included research published in mainstream scientific journals and conference proceedings. 2 Indexed journals mean scholarly journals indexed by abstract and citation databases such as Scopus and Web of Science, where the indexation implies journals with high scientific quality. Non-indexed journals are journals that fall outside of this indexation. More than half (57%) of these GPT-fabricated papers concerned policy-relevant subject areas susceptible to influence operations. To avoid increasing the visibility of these publications, we abstained from referencing them in this research note. However, we have made the data available in the Harvard Dataverse repository.

The publications were related to three issue areas—health (14.5%), environment (19.5%) and computing (23%)—with key terms such “healthcare,” “COVID-19,” or “infection”for health-related papers, and “analysis,” “sustainable,” and “global” for environment-related papers. In several cases, the papers had titles that strung together general keywords and buzzwords, thus alluding to very broad and current research. These terms included “biology,” “telehealth,” “climate policy,” “diversity,” and “disrupting,” to name just a few.  While the study’s scope and design did not include a detailed analysis of which parts of the articles included fabricated text, our dataset did contain the surrounding sentences for each occurrence of the suspicious phrases that formed the basis for our search and subsequent selection. Based on that, we can say that the phrases occurred in most sections typically found in scientific publications, including the literature review, methods, conceptual and theoretical frameworks, background, motivation or societal relevance, and even discussion. This was confirmed during the joint coding, where we read and discussed all articles. It became clear that not just the text related to the telltale phrases was created by GPT, but that almost all articles in our sample of questionable articles likely contained traces of GPT-fabricated text everywhere.

Evidence hacking and backfiring effects

Generative pre-trained transformers (GPTs) can be used to produce texts that mimic scientific writing. These texts, when made available online—as we demonstrate—leak into the databases of academic search engines and other parts of the research infrastructure for scholarly communication. This development exacerbates problems that were already present with less sophisticated text generators (Antkare, 2020; Cabanac & Labbé, 2021). Yet, the public release of ChatGPT in 2022, together with the way Google Scholar works, has increased the likelihood of lay people (e.g., media, politicians, patients, students) coming across questionable (or even entirely GPT-fabricated) papers and other problematic research findings. Previous research has emphasized that the ability to determine the value and status of scientific publications for lay people is at stake when misleading articles are passed off as reputable (Haider & Åström, 2017) and that systematic literature reviews risk being compromised (Dadkhah et al., 2017). It has also been highlighted that Google Scholar, in particular, can be and has been exploited for manipulating the evidence base for politically charged issues and to fuel conspiracy narratives (Tripodi et al., 2023). Both concerns are likely to be magnified in the future, increasing the risk of what we suggest calling evidence hacking —the strategic and coordinated malicious manipulation of society’s evidence base.

The authority of quality-controlled research as evidence to support legislation, policy, politics, and other forms of decision-making is undermined by the presence of undeclared GPT-fabricated content in publications professing to be scientific. Due to the large number of archives, repositories, mirror sites, and shadow libraries to which they spread, there is a clear risk that GPT-fabricated, questionable papers will reach audiences even after a possible retraction. There are considerable technical difficulties involved in identifying and tracing computer-fabricated papers (Cabanac & Labbé, 2021; Dadkhah et al., 2023; Jones, 2024), not to mention preventing and curbing their spread and uptake.

However, as the rise of the so-called anti-vaxx movement during the COVID-19 pandemic and the ongoing obstruction and denial of climate change show, retracting erroneous publications often fuels conspiracies and increases the following of these movements rather than stopping them. To illustrate this mechanism, climate deniers frequently question established scientific consensus by pointing to other, supposedly scientific, studies that support their claims. Usually, these are poorly executed, not peer-reviewed, based on obsolete data, or even fraudulent (Dunlap & Brulle, 2020). A similar strategy is successful in the alternative epistemic world of the global anti-vaccination movement (Carrion, 2018) and the persistence of flawed and questionable publications in the scientific record already poses significant problems for health research, policy, and lawmakers, and thus for society as a whole (Littell et al., 2024). Considering that a person’s support for “doing your own research” is associated with increased mistrust in scientific institutions (Chinn & Hasell, 2023), it will be of utmost importance to anticipate and consider such backfiring effects already when designing a technical solution, when suggesting industry or legal regulation, and in the planning of educational measures.

Recommendations

Solutions should be based on simultaneous considerations of technical, educational, and regulatory approaches, as well as incentives, including social ones, across the entire research infrastructure. Paying attention to how these approaches and incentives relate to each other can help identify points and mechanisms for disruption. Recognizing fraudulent academic papers must happen alongside understanding how they reach their audiences and what reasons there might be for some of these papers successfully “sticking around.” A possible way to mitigate some of the risks associated with GPT-fabricated scholarly texts finding their way into academic search engine results would be to provide filtering options for facets such as indexed journals, gray literature, peer-review, and similar on the interface of publicly available academic search engines. Furthermore, evaluation tools for indexed journals 3 Such as LiU Journal CheckUp, https://ep.liu.se/JournalCheckup/default.aspx?lang=eng . could be integrated into the graphical user interfaces and the crawlers of these academic search engines. To enable accountability, it is important that the index (database) of such a search engine is populated according to criteria that are transparent, open to scrutiny, and appropriate to the workings of  science and other forms of academic research. Moreover, considering that Google Scholar has no real competitor, there is a strong case for establishing a freely accessible, non-specialized academic search engine that is not run for commercial reasons but for reasons of public interest. Such measures, together with educational initiatives aimed particularly at policymakers, science communicators, journalists, and other media workers, will be crucial to reducing the possibilities for and effects of malicious manipulation or evidence hacking. It is important not to present this as a technical problem that exists only because of AI text generators but to relate it to the wider concerns in which it is embedded. These range from a largely dysfunctional scholarly publishing system (Haider & Åström, 2017) and academia’s “publish or perish” paradigm to Google’s near-monopoly and ideological battles over the control of information and ultimately knowledge. Any intervention is likely to have systemic effects; these effects need to be considered and assessed in advance and, ideally, followed up on.

Our study focused on a selection of papers that were easily recognizable as fraudulent. We used this relatively small sample as a magnifying glass to examine, delineate, and understand a problem that goes beyond the scope of the sample itself, which however points towards larger concerns that require further investigation. The work of ongoing whistleblowing initiatives 4 Such as Academ-AI, https://www.academ-ai.info/ , and Retraction Watch, https://retractionwatch.com/papers-and-peer-reviews-with-evidence-of-chatgpt-writing/ . , recent media reports of journal closures (Subbaraman, 2024), or GPT-related changes in word use and writing style (Cabanac et al., 2021; Stokel-Walker, 2024) suggest that we only see the tip of the iceberg. There are already more sophisticated cases (Dadkhah et al., 2023) as well as cases involving fabricated images (Gu et al., 2022). Our analysis shows that questionable and potentially manipulative GPT-fabricated papers permeate the research infrastructure and are likely to become a widespread phenomenon. Our findings underline that the risk of fake scientific papers being used to maliciously manipulate evidence (see Dadkhah et al., 2017) must be taken seriously. Manipulation may involve undeclared automatic summaries of texts, inclusion in literature reviews, explicit scientific claims, or the concealment of errors in studies so that they are difficult to detect in peer review. However, the mere possibility of these things happening is a significant risk in its own right that can be strategically exploited and will have ramifications for trust in and perception of science. Society’s methods of evaluating sources and the foundations of media and information literacy are under threat and public trust in science is at risk of further erosion, with far-reaching consequences for society in dealing with information disorders. To address this multifaceted problem, we first need to understand why it exists and proliferates.

Finding 1: 139 GPT-fabricated, questionable papers were found and listed as regular results on the Google Scholar results page. Non-indexed journals dominate.

Most questionable papers we found were in non-indexed journals or were working papers, but we did also find some in established journals, publications, conferences, and repositories. We found a total of 139 papers with a suspected deceptive use of ChatGPT or similar LLM applications (see Table 1). Out of these, 19 were in indexed journals, 89 were in non-indexed journals, 19 were student papers found in university databases, and 12 were working papers (mostly in preprint databases). Table 1 divides these papers into categories. Health and environment papers made up around 34% (47) of the sample. Of these, 66% were present in non-indexed journals.

Finding 2: GPT-fabricated, questionable papers are disseminated online, permeating the research infrastructure for scholarly communication, often in multiple copies. Applied topics with practical implications dominate.

The 20 papers concerning health-related issues are distributed across 20 unique domains, accounting for 46 URLs. The 27 papers dealing with environmental issues can be found across 26 unique domains, accounting for 56 URLs.  Most of the identified papers exist in multiple copies and have already spread to several archives, repositories, and social media. It would be difficult, or impossible, to remove them from the scientific record.

As apparent from Table 2, GPT-fabricated, questionable papers are seeping into most parts of the online research infrastructure for scholarly communication. Platforms on which identified papers have appeared include ResearchGate, ORCiD, Journal of Population Therapeutics and Clinical Pharmacology (JPTCP), Easychair, Frontiers, the Institute of Electrical and Electronics Engineer (IEEE), and X/Twitter. Thus, even if they are retracted from their original source, it will prove very difficult to track, remove, or even just mark them up on other platforms. Moreover, unless regulated, Google Scholar will enable their continued and most likely unlabeled discoverability.

A word rain visualization (Centre for Digital Humanities Uppsala, 2023), which combines word prominences through TF-IDF 5 Term frequency–inverse document frequency , a method for measuring the significance of a word in a document compared to its frequency across all documents in a collection. scores with semantic similarity of the full texts of our sample of GPT-generated articles that fall into the “Environment” and “Health” categories, reflects the two categories in question. However, as can be seen in Figure 1, it also reveals overlap and sub-areas. The y-axis shows word prominences through word positions and font sizes, while the x-axis indicates semantic similarity. In addition to a certain amount of overlap, this reveals sub-areas, which are best described as two distinct events within the word rain. The event on the left bundles terms related to the development and management of health and healthcare with “challenges,” “impact,” and “potential of artificial intelligence”emerging as semantically related terms. Terms related to research infrastructures, environmental, epistemic, and technological concepts are arranged further down in the same event (e.g., “system,” “climate,” “understanding,” “knowledge,” “learning,” “education,” “sustainable”). A second distinct event further to the right bundles terms associated with fish farming and aquatic medicinal plants, highlighting the presence of an aquaculture cluster.  Here, the prominence of groups of terms such as “used,” “model,” “-based,” and “traditional” suggests the presence of applied research on these topics. The two events making up the word rain visualization, are linked by a less dominant but overlapping cluster of terms related to “energy” and “water.”

The bar chart of the terms in the paper subset (see Figure 2) complements the word rain visualization by depicting the most prominent terms in the full texts along the y-axis. Here, word prominences across health and environment papers are arranged descendingly, where values outside parentheses are TF-IDF values (relative frequencies) and values inside parentheses are raw term frequencies (absolute frequencies).

Finding 3: Google Scholar presents results from quality-controlled and non-controlled citation databases on the same interface, providing unfiltered access to GPT-fabricated questionable papers.

Google Scholar’s central position in the publicly accessible scholarly communication infrastructure, as well as its lack of standards, transparency, and accountability in terms of inclusion criteria, has potentially serious implications for public trust in science. This is likely to exacerbate the already-known potential to exploit Google Scholar for evidence hacking (Tripodi et al., 2023) and will have implications for any attempts to retract or remove fraudulent papers from their original publication venues. Any solution must consider the entirety of the research infrastructure for scholarly communication and the interplay of different actors, interests, and incentives.

We searched and scraped Google Scholar using the Python library Scholarly (Cholewiak et al., 2023) for papers that included specific phrases known to be common responses from ChatGPT and similar applications with the same underlying model (GPT3.5 or GPT4): “as of my last knowledge update” and/or “I don’t have access to real-time data” (see Appendix A). This facilitated the identification of papers that likely used generative AI to produce text, resulting in 227 retrieved papers. The papers’ bibliographic information was automatically added to a spreadsheet and downloaded into Zotero. 6 An open-source reference manager, https://zotero.org .

We employed multiple coding (Barbour, 2001) to classify the papers based on their content. First, we jointly assessed whether the paper was suspected of fraudulent use of ChatGPT (or similar) based on how the text was integrated into the papers and whether the paper was presented as original research output or the AI tool’s role was acknowledged. Second, in analyzing the content of the papers, we continued the multiple coding by classifying the fraudulent papers into four categories identified during an initial round of analysis—health, environment, computing, and others—and then determining which subjects were most affected by this issue (see Table 1). Out of the 227 retrieved papers, 88 papers were written with legitimate and/or declared use of GPTs (i.e., false positives, which were excluded from further analysis), and 139 papers were written with undeclared and/or fraudulent use (i.e., true positives, which were included in further analysis). The multiple coding was conducted jointly by all authors of the present article, who collaboratively coded and cross-checked each other’s interpretation of the data simultaneously in a shared spreadsheet file. This was done to single out coding discrepancies and settle coding disagreements, which in turn ensured methodological thoroughness and analytical consensus (see Barbour, 2001). Redoing the category coding later based on our established coding schedule, we achieved an intercoder reliability (Cohen’s kappa) of 0.806 after eradicating obvious differences.

The ranking algorithm of Google Scholar prioritizes highly cited and older publications (Martín-Martín et al., 2016). Therefore, the position of the articles on the search engine results pages was not particularly informative, considering the relatively small number of results in combination with the recency of the publications. Only the query “as of my last knowledge update” had more than two search engine result pages. On those, questionable articles with undeclared use of GPTs were evenly distributed across all result pages (min: 4, max: 9, mode: 8), with the proportion of undeclared use being slightly higher on average on later search result pages.

To understand how the papers making fraudulent use of generative AI were disseminated online, we programmatically searched for the paper titles (with exact string matching) in Google Search from our local IP address (see Appendix B) using the googlesearch – python library(Vikramaditya, 2020). We manually verified each search result to filter out false positives—results that were not related to the paper—and then compiled the most prominent URLs by field. This enabled the identification of other platforms through which the papers had been spread. We did not, however, investigate whether copies had spread into SciHub or other shadow libraries, or if they were referenced in Wikipedia.

We used descriptive statistics to count the prevalence of the number of GPT-fabricated papers across topics and venues and top domains by subject. The pandas software library for the Python programming language (The pandas development team, 2024) was used for this part of the analysis. Based on the multiple coding, paper occurrences were counted in relation to their categories, divided into indexed journals, non-indexed journals, student papers, and working papers. The schemes, subdomains, and subdirectories of the URL strings were filtered out while top-level domains and second-level domains were kept, which led to normalizing domain names. This, in turn, allowed the counting of domain frequencies in the environment and health categories. To distinguish word prominences and meanings in the environment and health-related GPT-fabricated questionable papers, a semantically-aware word cloud visualization was produced through the use of a word rain (Centre for Digital Humanities Uppsala, 2023) for full-text versions of the papers. Font size and y-axis positions indicate word prominences through TF-IDF scores for the environment and health papers (also visualized in a separate bar chart with raw term frequencies in parentheses), and words are positioned along the x-axis to reflect semantic similarity (Skeppstedt et al., 2024), with an English Word2vec skip gram model space (Fares et al., 2017). An English stop word list was used, along with a manually produced list including terms such as “https,” “volume,” or “years.”

• Artificial Intelligence
• / Search engines

Cite this Essay

Haider, J., Söderström, K. R., Ekström, B., & Rödl, M. (2024). GPT-fabricated scientific papers on Google Scholar: Key features, spread, and implications for preempting evidence manipulation. Harvard Kennedy School (HKS) Misinformation Review . https://doi.org/10.37016/mr-2020-156

• / Appendix B

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This research has been supported by Mistra, the Swedish Foundation for Strategic Environmental Research, through the research program Mistra Environmental Communication (Haider, Ekström, Rödl) and the Marcus and Amalia Wallenberg Foundation [2020.0004] (Söderström).

Competing Interests

The authors declare no competing interests.

The research described in this article was carried out under Swedish legislation. According to the relevant EU and Swedish legislation (2003:460) on the ethical review of research involving humans (“Ethical Review Act”), the research reported on here is not subject to authorization by the Swedish Ethical Review Authority (“etikprövningsmyndigheten”) (SRC, 2017).

This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

Data Availability

All data needed to replicate this study are available at the Harvard Dataverse: https://doi.org/10.7910/DVN/WUVD8X

Acknowledgements

The authors wish to thank two anonymous reviewers for their valuable comments on the article manuscript as well as the editorial group of Harvard Kennedy School (HKS) Misinformation Review for their thoughtful feedback and input.